# Azure Databricks Reviews **Vendor:** Microsoft **Category:** [Big Data Analytics Software](https://www.g2.com/categories/big-data-analytics) **Average Rating:** 4.5/5.0 **Total Reviews:** 235 ## About Azure Databricks Azure Databricks is a unified, open analytics platform developed collaboratively by Microsoft and Databricks. Built on the lakehouse architecture, it seamlessly integrates data engineering, data science, and machine learning within the Azure ecosystem. This platform simplifies the development and deployment of data-driven applications by providing a collaborative workspace that supports multiple programming languages, including SQL, Python, R, and Scala. By leveraging Azure Databricks, organizations can efficiently process large-scale data, perform advanced analytics, and build AI solutions, all while benefiting from the scalability and security of Azure. Key Features and Functionality: - Lakehouse Architecture: Combines the best elements of data lakes and data warehouses, enabling unified data storage and analytics. - Collaborative Notebooks: Interactive workspaces that support multiple languages, facilitating teamwork among data engineers, data scientists, and analysts. - Optimized Apache Spark Engine: Enhances performance for big data processing tasks, ensuring faster and more reliable analytics. - Delta Lake Integration: Provides ACID transactions and scalable metadata handling, improving data reliability and consistency. - Seamless Azure Integration: Offers native connectivity to Azure services like Power BI, Azure Data Lake Storage, and Azure Synapse Analytics, streamlining data workflows. - Advanced Machine Learning Support: Includes pre-configured environments for machine learning and AI development, with support for popular frameworks and libraries. Primary Value and Solutions Provided: Azure Databricks addresses the challenges of managing and analyzing vast amounts of data by offering a scalable and collaborative platform that unifies data engineering, data science, and machine learning. It simplifies complex data workflows, accelerates time-to-insight, and enables the development of AI-driven solutions. By integrating seamlessly with Azure services, it ensures secure and efficient data processing, helping organizations make data-driven decisions and innovate rapidly. ## Azure Databricks Pros & Cons **What users like:** - Users highlight the **ease of use** of Azure Databricks, facilitating seamless integration and implementation for their projects. (7 reviews) - Users value the **superior interface and security features** of Azure Databricks, enhancing integration and usability. (6 reviews) - Users value the **straightforward integration with Azure services** of Databricks, enhancing efficiency and implementation speed. (5 reviews) - Users appreciate the **speedy implementation** of Azure Databricks, benefiting from its straightforward integration and efficient processing capabilities. (4 reviews) - Users appreciate the **efficient analytics capabilities** of Azure Databricks, enabling seamless integration and powerful data processing options. (3 reviews) - Powerful (3 reviews) - Scaling (3 reviews) - Time-Saving (3 reviews) - Usability (3 reviews) - Cloud Integration (2 reviews) **What users dislike:** - Users find the **complexity of the setup** challenging, especially for newcomers navigating cluster configurations and pricing. (3 reviews) - Users find the **difficult setup** of Azure Databricks challenging, particularly for newcomers navigating the initial configuration. (3 reviews) - Users face a **steep learning curve** with Azure Databricks, requiring time to navigate its complexities and manage costs effectively. (3 reviews) - Users report **slow performance** during cluster startup and parallel processing, impacting overall efficiency and testing speed. (3 reviews) - Users face challenges with **workflow issues** , particularly in monitoring and managing multiple pipeline executions effectively. (3 reviews) - Users find the **complex usability** of Azure Databricks challenging, especially for beginners navigating its extensive features. (2 reviews) - Cost Management (2 reviews) - Poor Customer Support (2 reviews) - Users often find **pricing unclear** , leading to unexpected costs if clusters aren't managed properly. (2 reviews) - Connectivity Issues (1 reviews) ## Azure Databricks Reviews ### 1. Azure Databricks efficient for large data, a bit rough on edges **Rating:** 4.5/5.0 stars **Reviewed by:** Wealth A. | Business Intelligence Analyst/ Designer, Financial Services, Enterprise (> 1000 emp.) **Reviewed Date:** April 24, 2026 **What do you like best about Azure Databricks?** What I like most about Azure Databricks is how it makes working with data feel straightforward without me having to overthink the setup. From my experience, I mostly use it for querying, transforming, and validating data, and it handles large datasets really well without slowing me down. I don’t have to worry too much about performance — I just write what I need, and it runs. I also like the flexibility of switching between SQL and PySpark depending on what I’m doing. It makes it easier to explore data and troubleshoot issues quickly without being stuck in one approach. The notebook environment is another big plus for me. I use it to organize my queries and logic in one place, so I can always go back, adjust things, or reuse parts without starting from scratch. Overall, it just makes my workflow cleaner and more efficient, especially when I’m working with large volumes of data and need quick, reliable results. **What do you dislike about Azure Databricks?** What I dislike about Azure Databricks, based on how I’ve used it, is mostly tied to day-to-day usability. When I’m working with files (especially around /dbfs), I sometimes run into seemingly random errors that aren’t very clear. It takes extra time to figure out what actually went wrong, which is frustrating when I’m just trying to get quick results. Debugging is another area that can slow me down. If a query or transformation doesn’t behave as expected, it isn’t always obvious where the issue is, so I end up spending more time tracing and narrowing things down than I’d like. The notebook environment is useful, but as a single notebook grows, it can get messy and harder to manage. If I’m not careful, it’s easy to lose structure and organization. Cost is also something I’ve had to keep an eye on. Even when I’m only testing or running queries, usage can add up quickly if resources aren’t managed properly. Overall, it works well, but there are still moments where it feels less intuitive than it should—especially when something goes wrong. **What problems is Azure Databricks solving and how is that benefiting you?** Azure Databricks mainly helps me work with large, scattered datasets in a way that’s actually manageable. In my experience, before using it, handling data across different sources or tools could get messy—especially when I needed to query, clean, and validate everything in a consistent way. With Databricks, I can do all of that in one place, which makes my process much simpler. It also takes away a lot of the stress around performance. I don’t have to worry as much about how my queries will scale as datasets grow—I can focus on writing what I need, and it handles the rest. That’s been especially helpful when I’m exploring or validating large volumes of data. Speed is another big plus. I can run queries quickly, test transformations, and iterate without long waits, which keeps my workflow moving and makes me more efficient. Overall, it makes my data work more straightforward and less fragmented. I spend less time jumping between tools or dealing with performance issues, and more time actually understanding and working with the data. ### 2. Comprehensive Data Management and Streamlined Setup **Rating:** 5.0/5.0 stars **Reviewed by:** Tej P. | DevOps Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** March 20, 2026 **What do you like best about Azure Databricks?** I use Azure Databricks to build and manage data pipelines. It provides all required services in a single place, like data engineering, SQL, and ML features. It helps me simply process large-scale data for enterprise projects, making Azure Databricks a valuable tool for me. The SQL features make it easy to query and analyze data quickly, and the ML capabilities support experimenting with models on the same platform. The initial setup is very easy; you just need to create a resource on the Azure portal by entering the resource group and Databricks workspace name with the rest of the default settings. **What do you dislike about Azure Databricks?** Cost optimization: it can be more optimized by providing the single cost monitoring dashboard by default for the workspace admins, as they have this budget feature in the preview for the account console only. **What problems is Azure Databricks solving and how is that benefiting you?** I use Azure Databricks to build and manage data pipelines, simplifying the processing of large-scale enterprise data. It lets me create scalable ETL pipelines, quickly query data with SQL, and experiment with ML models using Mosaic AI on the same platform. ### 3. All-in-One Data Platform with an Intuitive, User-Friendly Interface **Rating:** 5.0/5.0 stars **Reviewed by:** Mayuri K. | Product Management Fellow, Mid-Market (51-1000 emp.) **Reviewed Date:** May 01, 2026 **What do you like best about Azure Databricks?** It makes data easy and simple to understand even if we are not from technical background, i dont need to swap or switch different app or software now for data eng , analytics or data science all can be done in once now. The interface is very good and user friendly easy to understand tabs given , i have tried uploding a large set of data , uploading experience was very smooth and easy **What do you dislike about Azure Databricks?** Mostly, I got confused during the cluster setup. It was very difficult for me, and even with the settings I’m still struggling with it. **What problems is Azure Databricks solving and how is that benefiting you?** For me its helping mostly in getting faster insights, in tracking the perfomnce of the task assigned and outcomes on it ### 4. Azure Databricks: Scalable, Fast Collaboration with Seamless Azure Integration **Rating:** 4.5/5.0 stars **Reviewed by:** Elisa L. | Consultant Data&AI, Mid-Market (51-1000 emp.) **Reviewed Date:** April 30, 2026 **What do you like best about Azure Databricks?** What I like best about Azure Databricks is how well it combines scalability, speed, and collaboration in a single environment. It makes it easy to work with large datasets, build and run data pipelines efficiently, and support both engineering and analytics tasks without switching between too many tools. I also appreciate how smoothly it integrates with the broader Azure ecosystem, which makes it especially useful for end-to-end data processing and analytics workflows **What do you dislike about Azure Databricks?** One thing I dislike about Azure Databricks is that it can feel complex and not always immediately intuitive, especially at the beginning. The environment is powerful, but that also means there are many concepts, configurations, and moving parts to get used to before it feels really smooth. Another drawback is that, for some tasks, the setup and navigation can feel heavier than expected, which slows down simple workflows. In short, it is a very capable platform, but the learning curve and operational complexity can make it less straightforward than I would like. **What problems is Azure Databricks solving and how is that benefiting you?** Azure Databricks addresses the hassle of juggling separate tools for engineering, analytics, and AI by bringing everything into a single platform. That consolidation reduces friction and helps speed up delivery. For me, it means I can work more efficiently with large datasets, build pipelines, and collaborate in the same environment without constantly switching contexts. It also helps that the platform is built for scalable processing and integrated workflows, so the path from exploration to production feels much smoother and more consistent. ### 5. Azure Databricks: Unified, Scalable Data Platform That Boosts Productivity **Rating:** 5.0/5.0 stars **Reviewed by:** Suraj A. | Data Enigneer, Mid-Market (51-1000 emp.) **Reviewed Date:** February 04, 2026 **What do you like best about Azure Databricks?** What I like best about Azure Databricks is how it simplifies large-scale data processing while still giving flexibility to engineers. From my experience, the biggest advantage is the unified platform I can do data engineering, transformations, performance tuning, and even analytics in one place without jumping across multiple tools. The integration with Spark is seamless, and things like auto-scaling clusters, job scheduling, and notebook collaboration make day-to-day work much more efficient. I also appreciate features like Delta Lake handling ACID transactions, schema evolution, and time travel directly on data lakes makes production pipelines much more reliable. On top of that, optimizations like Adaptive Query Execution, auto-optimize, Z-ordering, and caching really help when working with large datasets. Another thing I like is how well it integrates with the Azure ecosystem whether it’s ADLS, ADF, Key Vault, or Unity Catalog for governance. It reduces a lot of setup overhead and makes deployments smoother across environments. Overall, it lets me focus more on solving data problems and performance tuning rather than worrying about infrastructure management. **What do you dislike about Azure Databricks?** One thing I dislike about Azure Databricks is that cost management can get tricky if clusters and jobs aren’t monitored closely. Because it’s so easy to spin up clusters and run large workloads, costs can increase quickly especially with auto-scaling or multiple parallel jobs running. So it requires good governance and monitoring in place. Another area is debugging and troubleshooting. While notebooks are great for development, debugging production job failures especially intermittent Spark or infrastructure issues can sometimes take time. Logs are available, but tracing the exact root cause across cluster events, Spark UI, and job runs isn’t always straightforward. I’ve also noticed that handling CI/CD and deployments (like moving notebooks, workflows, configs across environments) isn’t as smooth out of the box compared to traditional code repos. It’s improving with Databricks Asset Bundles and Repos, but still needs careful setup. That said, most of these are manageable with best practices cost controls, monitoring, and proper DevOps processes. **What problems is Azure Databricks solving and how is that benefiting you?** Azure Databricks is mainly solving the problem of processing and managing large-scale data efficiently in a unified environment. Before platforms like Databricks, handling big data required setting up separate tools for storage, compute, scheduling, and processing. It involved a lot of infrastructure management and integration effort. Databricks brings all of this together scalable Spark compute, collaborative notebooks, job orchestration, and optimized storage layers in one place. From a data engineering perspective, it solves challenges like processing huge volumes of data, handling complex transformations, and building reliable pipelines. Features like Delta Lake help address data consistency and reliability issues for example, ACID transactions, schema enforcement, and time travel make production data pipelines safer and easier to manage. It also solves performance problems. Optimizations like Adaptive Query Execution, caching, auto-scaling clusters, and partition pruning help process data faster without heavy manual tuning. How it benefits me personally: For me, it reduces the time spent on infrastructure setup and lets me focus more on data logic and optimization. I can quickly develop pipelines, test transformations in notebooks, and deploy jobs to production with better monitoring. It also improves productivity collaboration through shared notebooks, integration with Azure services like ADLS and ADF, and centralized governance through Unity Catalog make day-to-day work smoother. Overall, it helps me build scalable, reliable, and high-performing data solutions faster than traditional big data setups. ### 6. Lakebase Delivers Flexible Postgres Power for AI, Now with Autoscaling **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Computer & Network Security | Small-Business (50 or fewer emp.) **Reviewed Date:** March 27, 2026 **What do you like best about Azure Databricks?** Lakebase and API gateways. We use Lakebase as our primary database, and it has very strong capabilities for AI workloads. It’s also easy and flexible to work with because it’s a Postgres database. I think the addition of autoscaling databases is a really good improvement; instead of having static Compute Units assigned to each database, they can now scale automatically. I also like that with autoscaling you can set both the minimum and maximum CU, which gives you more control while still keeping things flexible. **What do you dislike about Azure Databricks?** Pricing is still not very clear, things are still measured in Compute units which is really hard to get down for pricing **What problems is Azure Databricks solving and how is that benefiting you?** We needed a platform that could cover our ML and data capabilities end to end. We use Lakebase as our primary data system, and it’s been easy to port work into notebook capabilities since Databricks is very strong with Spark. Their AI gateway also helps ensure we can run AI workloads on our data, which was important for us as well. ### 7. A Powerful and Reliable Platform for Scalable Data Engineering **Rating:** 5.0/5.0 stars **Reviewed by:** NOOR A. | Data Engineer, Information Technology and Services, Enterprise (> 1000 emp.) **Reviewed Date:** October 18, 2025 **What do you like best about Azure Databricks?** What I like best about Azure Databricks is how seamlessly it integrates with the Azure ecosystem — especially with services like Data Lake, Synapse, and Data Factory. It provides an excellent balance between ease of use and advanced capabilities, allowing both technical and non-technical users to collaborate in a single environment. The notebooks are intuitive and support multiple languages such as SQL, Python, and R, which makes implementation and experimentation smooth. I use it frequently for building and managing data pipelines, running transformations, and developing machine learning models. The platform’s scalability, auto-scaling clusters, and managed Delta Lake features make handling large datasets efficient. Customer support is generally helpful and the platform continues to evolve with frequent updates that add even more useful features. **What do you dislike about Azure Databricks?** Although Azure Databricks is powerful, a few areas could be improved. The initial setup and environment configuration can be slightly complex for new users, and cluster startup times can sometimes be slow. The pricing structure also requires careful monitoring — costs can increase quickly if clusters aren’t optimized or auto-terminated properly. While the interface is robust, it could be more beginner-friendly, and notebook version control could be smoother. Customer support response time can vary depending on the issue severity. Still, once you get accustomed to the environment, it’s a highly capable and dependable platform for daily data workloads and analytics. **What problems is Azure Databricks solving and how is that benefiting you?** Azure Databricks has addressed several major data challenges within our organization. Previously, handling large datasets, integrating various data sources, and executing complex transformations were both time-consuming and prone to errors. With Databricks, I am able to develop scalable ETL pipelines and automate data workflows more efficiently, which has greatly reduced manual work and shortened processing times. The platform also offers a collaborative environment where data engineers and analysts can work together smoothly, enhancing productivity and minimizing miscommunication. Its integration with Azure services such as Data Lake, Data Factory, and Synapse ensures seamless data movement throughout our ecosystem. This has enabled us to deliver reliable, high-quality datasets more quickly for reporting, analytics, and machine learning projects, ultimately supporting better business decisions and greater operational efficiency. ### 8. Effortless Data Processing and Seamless Azure Integration **Rating:** 4.5/5.0 stars **Reviewed by:** Akshat G. | Programmer Analyst, Information Technology and Services, Small-Business (50 or fewer emp.) **Reviewed Date:** December 03, 2025 **What do you like best about Azure Databricks?** The platform manages large-scale data processing with impressive smoothness, and its interface becomes quite user-friendly after a short learning curve. Integrating it with other Azure services is straightforward, which significantly speeds up the implementation process. I appreciate the variety of features available for ETL and analytics, allowing us to use it regularly for a range of different workloads. When problems arise, the documentation and support resources are generally sufficient to help resolve issues quickly. **What do you dislike about Azure Databricks?** Sometimes, the platform can seem a little complicated for newcomers, and it may take some time for clusters to start up. Managing costs is not always straightforward, and certain features require additional configuration. While support is generally helpful, response times can occasionally be slow. **What problems is Azure Databricks solving and how is that benefiting you?** This tool enables us to process large datasets efficiently and construct dependable ETL pipelines. By consolidating data cleaning, transformation, and analytics into a single collaborative platform, it streamlines our workflow. The integration with Azure storage and other services is a significant time-saver, and the increased processing speed has a direct positive impact on our reporting and decision-making. ### 9. Efficient, Scalable Data Processing Powerhouse **Rating:** 4.5/5.0 stars **Reviewed by:** Muzammil A. | IT Technician, IT Infrastructure Operations, Mid-Market (51-1000 emp.) **Reviewed Date:** March 30, 2026 **What do you like best about Azure Databricks?** I use Azure Databricks for data processing, ETL, and analytics on large datasets. I like its scalability and easy collaboration in one unified platform. I appreciate its fast performance, seamless integration with other Azure services, and user-friendly notebooks. The initial setup was very easy, especially with the guidelines provided on the website. **What do you dislike about Azure Databricks?** Cost management, fast cluster startup times, and a more intuitive UI for beginners. **What problems is Azure Databricks solving and how is that benefiting you?** I use Azure Databricks to efficiently process large datasets, simplify ETL workflows, and enable fast, scalable data analysis on one platform. ### 10. My review after using Azure Databricks **Rating:** 4.5/5.0 stars **Reviewed by:** Julius S. | A student at the University of the People, Higher Education, Mid-Market (51-1000 emp.) **Reviewed Date:** July 27, 2025 **What do you like best about Azure Databricks?** Azure Databricks is a great platform that offers a robust environment for querying large datasets through Apache spark. I especially appreciate how effortless it integrate with Azure storage account and notebooks making big data analytics efficient and scalable. Databricks built in version control combined with smooth GitHub integration makes collaboration and code management easy. It's one of the best setup I have worked with. **What do you dislike about Azure Databricks?** The setup and cluster configuration is sometimes confusing and time consuming. **What problems is Azure Databricks solving and how is that benefiting you?** One major benefits of using Azure Databricks is that it provides a platform for all data experts in a single environment where collaboration is seamless and scalable. My team (inc. data scientist, engineers and analyst) easily work together in this unified platform to ingest, process, analyze and visualize data effortlessly. Another benefit is the speed and performance to run large scale computations without worrying about infrastructure complexity ### 11. “Robust cloud-based big data platform for migration and day-to-day analytics” **Rating:** 5.0/5.0 stars **Reviewed by:** Lakshmi B. | Software Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** September 18, 2025 **What do you like best about Azure Databricks?** Azure Databricks gave us a unified platform to run our Spark workloads on top of Azure Data Lake Storage Gen2. We could migrate our on-prem Hadoop data and pipelines into the cloud with minimal re-engineering. Its managed clusters, autoscaling, notebooks, and tight integration with Azure services (ADLS, Key Vault, ADF) saved a lot of infrastructure and maintenance effort. PySpark notebooks made development and debugging much easier compared to our previous setup. **What do you dislike about Azure Databricks?** Cluster start-up times can still be slow for quick tests. Pricing is consumption-based and can become expensive if clusters are left running or poorly sized. Some enterprise features (e.g., fine-grained security, monitoring) require extra configuration. And compared to on-prem Hadoop, there’s a learning curve for workspace permissions and DevOps automation. **What problems is Azure Databricks solving and how is that benefiting you?** It allowed us to move legacy Hadoop/HDFS workloads to the cloud without rewriting all the code. We now process large volumes of structured and unstructured data using PySpark on a scalable managed cluster, store it in ADLS Gen2, and orchestrate everything through ADF. This reduced infrastructure management overhead, improved performance, and gave teams a collaborative environment for ETL and analytics. ### 12. Jupyter & Unity Catalog Shine, Genie AI Needs Improvement **Rating:** 5.0/5.0 stars **Reviewed by:** Drishti C. | Senior data Analyst, Mid-Market (51-1000 emp.) **Reviewed Date:** October 23, 2025 **What do you like best about Azure Databricks?** Really like the Jupyter notebook system & Unity Catalog lineage **What do you dislike about Azure Databricks?** Genie - Ai Assistant can have better accuracy **What problems is Azure Databricks solving and how is that benefiting you?** The multiple coding language in notebook style implementation & crazy governance tracking via UC. I have not tried MLFlow & model serving yet but I have heard that it's great in version controlling & uptime. ### 13. Review for Azure Databricks **Rating:** 5.0/5.0 stars **Reviewed by:** G P. | Data Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** June 19, 2025 **What do you like best about Azure Databricks?** The best about azure databricks is very easy to integrate to any cloud, rdbms or any other software services. It is very easy to use and to implement. The frequency of use is so high in my project. There are many number of features in azure databricks. Also it is easy to integrate with gitlab, hive, rdbms etc for any ETC processes. **What do you dislike about Azure Databricks?** There is nothing that i dislike about Azure databricks as of 4 yr experience. **What problems is Azure Databricks solving and how is that benefiting you?** The problem which is solved by azure Databricks is, it is having very human friendly ui to easily write the code, schedule workflow, integrate Git. Also for easy data processing, analytics and machine learning tasks. ### 14. Process Specialist **Rating:** 5.0/5.0 stars **Reviewed by:** SAI SHARAN C. | Market Research Consultant- Freelancer , Mid-Market (51-1000 emp.) **Reviewed Date:** December 09, 2022 **What do you like best about Azure Databricks?** Easy to write programs a d executes all scripts , user friendly application **What do you dislike about Azure Databricks?** Everything ok it was updating day by day making every user free and stress less tool **What problems is Azure Databricks solving and how is that benefiting you?** It's solved all my issue of data and scripts ### 15. Azure Databricks is One of the Best Analytical Software **Rating:** 4.0/5.0 stars **Reviewed by:** Yash U. | data engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** September 16, 2025 **What do you like best about Azure Databricks?** In Azure Databricks, you can have multiple layers of Security in those tables as well as there use interface is far more better that Teradata **What do you dislike about Azure Databricks?** In Azure Databricks Likely the Cost is the of the factory which poeple though as it can be one of factor **What problems is Azure Databricks solving and how is that benefiting you?** Azure Databricks is helpling the old system to mordnize them also includes the AI capabities in those Data which are we have and also the connectivity wise Azure Databricks can be connected to any software like Quilk, Tableau, or SAP etc ### 16. Outstanding Databricks Experience—Best Implementation Yet **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Manufacturing | Mid-Market (51-1000 emp.) **Reviewed Date:** January 13, 2026 **What do you like best about Azure Databricks?** This is the best implementation of Databricks I could have hoped for. **What do you dislike about Azure Databricks?** Occasionally, when I put my laptop to sleep, my Azure Databricks sessions do not reconnect quickly. **What problems is Azure Databricks solving and how is that benefiting you?** We rely on Azure Databricks to manage all of our AI and machine learning workloads. ### 17. Impressive Data Transfer, But Room for Improvement **Rating:** 2.5/5.0 stars **Reviewed by:** Jhcghbv K. | Teacher , Mid-Market (51-1000 emp.) **Reviewed Date:** November 30, 2025 **What do you like best about Azure Databricks?** Huge data celan transfer. And this is mainly use from banking **What do you dislike about Azure Databricks?** This is the complex setup . Do not optimisation **What problems is Azure Databricks solving and how is that benefiting you?** My huge data clean transfer ### 18. Azure Is amazing **Rating:** 5.0/5.0 stars **Reviewed by:** Adnan J. | BI Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** June 26, 2025 **What do you like best about Azure Databricks?** Its like a one stop shop for everything. **What do you dislike about Azure Databricks?** Sometimes the use of python with sql gets complicated. **What problems is Azure Databricks solving and how is that benefiting you?** I am using 3rd party API's to stage my data into databricks and using that data as a downstream for tableau reporting. ### 19. A complete data tool for every requirement and use case **Rating:** 5.0/5.0 stars **Reviewed by:** Vikram K. | Data Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** August 02, 2025 **What do you like best about Azure Databricks?** They are improving the existing features and adding new features for easy integration. **What do you dislike about Azure Databricks?** Some features are not very intuitive and user friendly live crearting secret scope. **What problems is Azure Databricks solving and how is that benefiting you?** Running big clusters for spark becomes very easy instead of on-prem systems. Its serverless services are helpfull in reducing cost for exploratory data analysis. ### 20. Databricks in all you need for any work related to data **Rating:** 5.0/5.0 stars **Reviewed by:** Aman Kumar K. | Software Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** October 26, 2024 **What do you like best about Azure Databricks?** There are lots of things for example: 1. An excellent Data Engineering tool. 2. Support multiple languages like Scala, Python, R and SQL. 3. Support Analytical work as well. 4. We can create and deploy Machine Learning Models. 5. Very fast as build on top on Apache Spark. 6. Multi language support within one Notebook. 7. Compute is extremely faster and cluster options are available like All-Purpose and Job Clusters. 8. Function like cluster pools are very useful. 9. Using it daily and loving it's UI and functinalities. **What do you dislike about Azure Databricks?** I am using Databricks since 2019, and have no complaint or issues as such. There is one area where more functionality can be added is in FS command (File System). More functionality can give more flexibility to the developers. **What problems is Azure Databricks solving and how is that benefiting you?** We are using Databricks for all data related tasks, be it for creation of Data Pipeline for Data Engineering, for Data Analytics to present reports to business user and for machine learning tasks as well. Along with that scheduling jobs and pipelines. ### 21. Efficient but Needs More Compute Power **Rating:** 4.5/5.0 stars **Reviewed by:** firesavant f. **Reviewed Date:** October 02, 2025 **What do you like best about Azure Databricks?** I appreciate how easy it was to start using Azure Databricks online, which made the initial setup straightforward. The ability to create jobs that run on serverless computes has been a huge time-saver, significantly speeding up processing tasks. Running Python files and notebooks efficiently on this platform enhances my productivity. **What do you dislike about Azure Databricks?** I find configuring Azure Databricks and connecting it to Visual Studio Code to be quite challenging. Additionally, I feel that the parallel processing speed could be improved, as it currently doesn't meet my expectations for efficiency. I also encounter restrictions with the DLT pipeline, as it limits the keywords I can use with SQL, complicating my workflow. **What problems is Azure Databricks solving and how is that benefiting you?** I use Databricks for serverless computing, speeding up Python file processing and notebook execution. ### 22. Unified Lakehouse **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Consumer Goods | Enterprise (> 1000 emp.) **Reviewed Date:** October 21, 2024 **What do you like best about Azure Databricks?** Unified data eco system capability for DE and ML **What do you dislike about Azure Databricks?** Steep learning curve, still evolving on basics **What problems is Azure Databricks solving and how is that benefiting you?** Gives you unified lakehouse capability to break down silos in data teams. Being able to create E2E solution in one solution rather than using many solution from seperate companies ### 23. "Best data processing and Analytic platform": Azure Databricks review **Rating:** 5.0/5.0 stars **Reviewed by:** Shubham T. | Data Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** May 15, 2024 **What do you like best about Azure Databricks?** About azure Databricks what I like most is,it's ability of providing multiple services for data like data processing,management,analysis. It is extensively used by data engineer for data extract,tranform and load in professional work. It allows user to write basic and advanced transformation logic within notebook. Also clustered is automatically managed by service provider thus user do not need to worry about it. And the GUI and ease of use is simple. High Customer Support. **What do you dislike about Azure Databricks?** Sometime pricing structure create problem for small business. Starting cluster with high dataset take more time to get started. **What problems is Azure Databricks solving and how is that benefiting you?** Databricks helps to handle big data with maximum potential,capacity and with ease ,and it very easy to create connection from databricks to snowflake for data loading. In notebook using pyspark,SQL,python language etc we can create complex transformation logic in databricks,which is very helpful data engineer and data scientist. ### 24. Databricks reviews- Best data analytics tool **Rating:** 5.0/5.0 stars **Reviewed by:** Sanjana R. | Analyst, Enterprise (> 1000 emp.) **Reviewed Date:** April 07, 2024 **What do you like best about Azure Databricks?** It is very easy to use and we do not need to manage the cluster configuration as it is properly automated. It is used by datascientis and data engineer for data transformation and Extract tranform and load (ETL).. I like the Graphical user interfacer and it allow me to use with azure cloud platforms. Also it is less costly then other tools like snowflakes. **What do you dislike about Azure Databricks?** When we are using it with large dataset then it get costly. And the major thing that I dislike is,more dependency on microsoft azure cloud provider. **What problems is Azure Databricks solving and how is that benefiting you?** It is very helful in writing transformation scripts inside notebbok using python or sql language. Data loading to snowflake is very easy through databricks. Large volumes of data processing efficiently might be challenging but using Azure Databricks it become easy to handle big data with ease,as it built on Apache Spark that offers scalable and distributed data processing capabilities. ### 25. My Experience with Azure Databricks as Platform Integration Engineer **Rating:** 5.0/5.0 stars **Reviewed by:** Samshitha V. | Quality Engineering Enabler, Mid-Market (51-1000 emp.) **Reviewed Date:** September 28, 2024 **What do you like best about Azure Databricks?** There are many ETL tools , but nothing comes near Databricks. We can have n number of complex transformations that can be done in datbricks notebooks using pyspark and Unity catalog is the best feature. Customer support is very good, had to connect with them for some external integrations like prefect. **What do you dislike about Azure Databricks?** Costing is more, but if you have proper policies in place as organization and have control over cluster usage then can easily overcome high cost. **What problems is Azure Databricks solving and how is that benefiting you?** Many of our application teams needs ETL processing. So Databricks integartion to our platform made their works easy. ### 26. My experience is fairly nice **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Enterprise (> 1000 emp.) **Reviewed Date:** January 08, 2025 **What do you like best about Azure Databricks?** Its big data processing capablity and multiple language interface in one notebook **What do you dislike about Azure Databricks?** Workflows monitoring and ui is not mature enough to handle multiple pipeline exceution **What problems is Azure Databricks solving and how is that benefiting you?** Big data processing and it saves lot of our time and space and boost our descion making capablity ### 27. A great collaboration platform **Rating:** 5.0/5.0 stars **Reviewed by:** Pang L. | Machine Learning Engineer, Small-Business (50 or fewer emp.) **Reviewed Date:** July 19, 2024 **What do you like best about Azure Databricks?** It is a single platform covering data engineering and machine learning. People in different roles, such as data scientists, machine learning engineers, and data engineers, can conveniently work together on it. **What do you dislike about Azure Databricks?** There is one issue I really hope they can fix. The widgets panel settings of notebooks default to "Run Accessed Commands," which I find really inconvenient. I strongly suggest they change it to "Do Nothing." **What problems is Azure Databricks solving and how is that benefiting you?** Machine learning R&D; data pipeline. I use Databricks every day. ### 28. Best product for data driven activities **Rating:** 5.0/5.0 stars **Reviewed by:** Arpit K. | Associate Data Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** June 28, 2024 **What do you like best about Azure Databricks?** The best part about Databricks is we can use many languages like sql , python , scala in same platform for our work , secondly UI is best . **What do you dislike about Azure Databricks?** As such nothing I only feel one drawback is thst they are not having there own storage **What problems is Azure Databricks solving and how is that benefiting you?** We were using many platforms like PBI , SQL , IDLE but we got all on same platform after using this product. ### 29. Amazing **Rating:** 5.0/5.0 stars **Reviewed by:** Brandon P. | Manager, Data Engineering, Mid-Market (51-1000 emp.) **Reviewed Date:** November 18, 2024 **What do you like best about Azure Databricks?** It's designed for engineers! Makes accessing cloud cluster so convenient! **What do you dislike about Azure Databricks?** It's hard to understand full cost at times. **What problems is Azure Databricks solving and how is that benefiting you?** It is our heart of our data platform at the organization. From reporting to advanced analytics ### 30. DataBricks for Data Engineers and ML Jobs **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Health, Wellness and Fitness | Small-Business (50 or fewer emp.) **Reviewed Date:** December 13, 2023 **What do you like best about Azure Databricks?** Easy To use, no need to worry about the cluster configurations. its widenly used azures for Data transformation and ETL jobs its useful for Dataengineers and Datascience Projects. new and enhanced technology are implementing like Unified analytics, autoloader and Machine Learning Service Integaration. we can use for realtime data streaming using apache kafka and structured streaming. cost wise less compared to other tools like snowflake. **What do you dislike about Azure Databricks?** Its more dependent on the microsoft azure cloud provider Its more cost when we are trying to move the large dataset in and around of the azure cloud Supporing team are less action taking, whenever we raise the tickets for any issues on databricks they will ask us to escalate so it will reach to higher team then they will take the action on the issues, so it will be very less moving on support Team. Other tools are more optimised and more User friendly. **What problems is Azure Databricks solving and how is that benefiting you?** We developed the Pipelines for Moving and transforming the data between blob to snowflake we applied complex transformation on the data and also data available in delta tables. connectivity to snowlflake and loading to the datawarehouse. ### 31. Is Azure Databricks best? **Rating:** 5.0/5.0 stars **Reviewed by:** prasadgoud a. | System Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** August 28, 2024 **What do you like best about Azure Databricks?** This is the one and only data lake house platform covers everything a DataEngineer needs. Unity catalog feature is best as it helps us maintain Medalian architecture. Maintaining notebooks is easy. **What do you dislike about Azure Databricks?** Only thing is its very costly, so need to constantly monitor resource usage. **What problems is Azure Databricks solving and how is that benefiting you?** Helps in developing day to day ETL processes and makes it easy to run notebooks and jobs ### 32. Azure Databricks: A great tool **Rating:** 5.0/5.0 stars **Reviewed by:** Krati B. | Consultant Data Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** November 16, 2023 **What do you like best about Azure Databricks?** Azure databricks is a great amalgamation of azure cloud services and databricks. Its quite easy to setup and I can do everything in my azure cloud platform only. The best thing about it is we need not manage the cluster, its properly automated. Its great how I can use Azure VMs along with databricks **What do you dislike about Azure Databricks?** So far I have not found anything to dislike. Azure Databricks is definately a plus to both Databricks and Azure users **What problems is Azure Databricks solving and how is that benefiting you?** Being a data engineer, I have faced lot of challenges with data transformation. Azure Databricks has definately come to the rescue as it has ample libraries and such cool features as time-travel and versioning, it helps a lot and mostly saves me from any wrong commits in my code. It also helps me handle different kinds of files quite efficiently and let me deliver clean files to the client ### 33. One of the best powerful engine to store and process large datasets **Rating:** 5.0/5.0 stars **Reviewed by:** Priyanshu A. | Data Analyst intern, Mid-Market (51-1000 emp.) **Reviewed Date:** February 23, 2024 **What do you like best about Azure Databricks?** There are many things which I like best about Azure Databrick i.e., it is one of the best engine in the cloud to store and process large datasets. I have easily integrated this with Azure data lake storage and Azure SQL database. **What do you dislike about Azure Databricks?** I don not see any issue or concerns about Azure Databricks except costing which I thought is a little bit high in comparison with its competitors. **What problems is Azure Databricks solving and how is that benefiting you?** Handling large volumes of data efficiently is a very big challenge in big data processing. Azure Databricks helps in storing and processing this large dataset within no time. I have easily integrated with Azure Storage, Azure SQL Database and Azure Machine Learning. With the help of Azure Machine Learning, I have done predictive modelling in quite less time. ### 34. I have a robust background in utilizing Azure Databricks for big data and analytics projects. **Rating:** 5.0/5.0 stars **Reviewed by:** Aziz Rahman H. | Freelance Translator, Small-Business (50 or fewer emp.) **Reviewed Date:** January 03, 2024 **What do you like best about Azure Databricks?** As a machine learning model developed by OpenAI, I don't have personal experiences or preferences. However, I can provide information based on common user feedback. Many users appreciate several aspects of Azure Databricks, including: Collaborative Environment: Azure Databricks provides a collaborative workspace where data scientists, engineers, and analysts can work together seamlessly, fostering collaboration and knowledge sharing. **What do you dislike about Azure Databricks?** While Azure Databricks is a widely used platform with numerous advantages, there are some considerations and potential drawbacks that users may encounter: Cost: Using Azure Databricks can be expensive, especially for large-scale and resource-intensive workloads. Users should carefully monitor their usage to avoid unexpected costs. Learning Curve: For users new to big data processing and Apache Spark, there might be a learning curve associated with mastering the intricacies of Databricks and Spark-based workflows. **What problems is Azure Databricks solving and how is that benefiting you?** Azure Databricks solves various challenges related to big data processing, analytics, and machine learning. The benefits derived from using Azure Databricks depend on the specific use case and the goals of the organization or individual. Here are some common problems that Azure Databricks addresses and the associated benefits: Scalable Data Processing: Problem: Processing large volumes of data efficiently can be challenging. Benefit: Azure Databricks, built on Apache Spark, offers scalable and distributed data processing capabilities, allowing users to handle big data workloads with ease. ### 35. Databricks review **Rating:** 4.5/5.0 stars **Reviewed by:** Dinesh S. | Software Engineer, Computer Software, Enterprise (> 1000 emp.) **Reviewed Date:** September 22, 2023 **What do you like best about Azure Databricks?** It can be used as a working session for writing SQL,python queries by mapping the database in the databricks.the output of the queries can be downloaded in Excel and in other formats such as CSV ,is the best features which helps for analysing the data.python commands can also be executed using %py by simply changing the language from SQL to python.Therw are additional features like uploading the wheel file generated in a dbfs path which is easier to use in order to get the latest code in github **What do you dislike about Azure Databricks?** While copy pasting the commands from one cell to another ,the header of the command is not copied.we have to manually redo again .Another backlogging issue is we need to start the cluster manually after a certain period and it takes larger time to get active.we cannot able to drag the command in between the commands. **What problems is Azure Databricks solving and how is that benefiting you?** We can use both python and SQL at a time which helps in integrating multiple codes at a time.creating separate notebooks for each tasks helps in developing the codes ,writing the SQL test cases , performing unit test cases.also cloning the notebooks helps in reexecuting the same set of queries when a new data comes into the database table. ### 36. The best program for data management that exists. **Rating:** 4.0/5.0 stars **Reviewed by:** Marcy H. | Freelance Social Media Specialist, Small-Business (50 or fewer emp.) **Reviewed Date:** December 07, 2023 **What do you like best about Azure Databricks?** Azure Databricks is awesome. Its ability to simplify data analysis is unparalleled. I love the intuitive interface and real-time collaboration it offers, facilitating agile decision making. In short, Azure Databricks has transformed the way we approach data analysis. Its versatility, power and the way it accelerates decision making make it the undisputed choice for our team. We are excited for the future and the innovations that will continue to improve our experience with this platform. **What do you dislike about Azure Databricks?** Although Azure Databricks is incredibly powerful, sometimes the learning curve can be steep. It would be great to have more training resources built in to make it easier to onboard new users. **What problems is Azure Databricks solving and how is that benefiting you?** At our company, Azure Databricks has been the key to solving complex data analysis problems. We have improved operational efficiency and optimized resources, resulting in significant savings. The benefits are palpable: greater agility, faster insights and more informed decisions. ### 37. Azure Data Bricks : an excellent symphony between Apache Spark and Cloud technology **Rating:** 4.0/5.0 stars **Reviewed by:** Nida S. | System Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** January 23, 2024 **What do you like best about Azure Databricks?** Harness the power of a top analytics system (Apache Spark) with the ease and flexibility of a cloud platform (Azure) and seamless integration with Power BI to transform the massive amounts of data into visualization .One click deployment adds to its advantages. **What do you dislike about Azure Databricks?** User needs to be aware of the billing and monitor the usage pattern well to avoid incurring high cost .UI could do with few more enhancements.Also more in depth learning material w and an active support community would be very advantageous for new users. **What problems is Azure Databricks solving and how is that benefiting you?** I use it to integrate, transform and process the Big Data before using it as source in my Power BI dashboard to generate visualization for business users ### 38. Databricks - Unleashing the Power of Modern Lakehouse with Unified governance !!! **Rating:** 4.5/5.0 stars **Reviewed by:** Senthil K. | Senior Cloud Solution Architect - Accenture Data & AI (Applied Intelligence), Enterprise (> 1000 emp.) **Reviewed Date:** October 19, 2023 **What do you like best about Azure Databricks?** Delta Live tables Schema evolution feature in Autoloader Unity Catalog with unified governance Data quality expectations as part of DLT CDC - Change data feed option DELTA format - time travel, ACID & VACCUM capabilities Serverless SQL warehouse with Photon acceleration Delta Sharing through marketplace Good community support **What do you dislike about Azure Databricks?** Cost of databricks cluster for all-purpose cluster data engineering workpsace cluster is not serverless unless DLT is used DLT has some extra cost associated with it Even using cluster pool, start up time of job cluster is taking some time But all these challenges are currently encountered through DLT serverless options **What problems is Azure Databricks solving and how is that benefiting you?** CDC - Incremental delta tables with Change data feed is easier Continous streaming of data using DLT pipelines Schema evolution issues can be sorted out when upstream schema changes Unity Catalog with unified governance for fine grained access row level & column level control wth dynamic views Data quality expectations built-in feature for DLT pipelines DELTA format supports time travel, ACID & VACCUM capabilities Serverless SQL warehouse with Photon acceleration for faster inetractive analytics & concurrent access by multiple users Delta Sharing through marketplace through producers & consumers ### 39. Empowering Data with Azure Databricks **Rating:** 4.5/5.0 stars **Reviewed by:** Siddharth S. | Enterprise (> 1000 emp.) **Reviewed Date:** November 03, 2023 **What do you like best about Azure Databricks?** It's like magic for data. It makes big data and analytics easy, and we can all work together seamlessly. It's user-friendly, powerful, and scales like a champ. **What do you dislike about Azure Databricks?** The prricing structure, which can get a bit complex. It requires careful management to ensure you're not surprised by unexpected costs, especially when dealing with large datasets and workloads. While the platform offers great value, transparent pricing would be a welcome improvement. **What problems is Azure Databricks solving and how is that benefiting you?** It simplifies the most complex data processing tasks, making them more manageable and efficient as this saves us valuable time and resources and it also promotes collaboration, Ensures scalability, Boosts performance, Unlocks data-driven insights. ### 40. Unified Data platform - Databricks **Rating:** 4.0/5.0 stars **Reviewed by:** Naresh N. | Associate - Capital Markets, Mid-Market (51-1000 emp.) **Reviewed Date:** October 08, 2023 **What do you like best about Azure Databricks?** The most impressive thing which I liked about the Azure Databricks is that It helps to simply our Data science and Data engineering workloads. As we use Azure as our cloud provider including Databricks from the same vendor allows us to do all billing without any hazel. The optimised notebook in Databricks help us to write efficient pyspak code which can handle big data processing like a charm. Also it get easily integrated with Azure DataFactory to build some pipeline for automation purpose. **What do you dislike about Azure Databricks?** 1. We use Azure Databricks to build som code in notebook which can process and transform complex data problems, but when it comes to automate, the Databricks native workflow and job scheduler doesn't give that much features when comparing to other platforms like Azure DataFactory. 2. When we use SQL environment for data warehousing purpose, since it use Photon engine the upfront cost of having it is much higher than other platforms like snowflake. **What problems is Azure Databricks solving and how is that benefiting you?** We used Azure Databricks to handle big data analytics problems. We developed code using notebook which contains complete data integration and data transform steps. Using the product along with Azure give use more flexibility in terms on management and billing as all the resources are under same billing account. ### 41. Having great experience working with Databricks! **Rating:** 4.5/5.0 stars **Reviewed by:** Pratiksha S. | Associate Consultant, Mid-Market (51-1000 emp.) **Reviewed Date:** December 21, 2023 **What do you like best about Azure Databricks?** As Platform engineer it's easy to use and understand databricks. User friendly portal. Workflows and Computes I am using on daily basis. Catalogs gives very clear feature of datalog, schemas and tables. Databricks customer support team is very helpful. **What do you dislike about Azure Databricks?** No dislike till now. But sometimes ganglia matrics and logs are not coming poroperly. **What problems is Azure Databricks solving and how is that benefiting you?** Processing data very easily. we can create multiple jobs and cluster. It helps to connect to store, share, analyze, models. ### 42. Databricks - The unified place for all Analytics you need **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Retail | Enterprise (> 1000 emp.) **Reviewed Date:** December 07, 2023 **What do you like best about Azure Databricks?** It is cool. It gives you everything you need to perform analytics, ranging from Data engineering workspace, to features specially for ML and data science models. It has features like running the scripts in sql, python, scala and R, which is a huge flexibility for a developer. These days they have given option to create dashboards also, it means one can create on-fly dashboards to analyse their datasets. Personally, i love their command like interface (like jupyter notebook) and the way we could configure clusters on-fly. Unity catalog is the recent feature which i am working on. **What do you dislike about Azure Databricks?** While Azure Databricks is a robust platform, occasional user interface responsiveness issues have been noted. Additionally, the initial learning curve may pose challenges for new users, affecting ease of onboarding and usability. Specifically, one need to learn the basics of the various specific techs, like parameterization, configuration of clusters, running jobs on workflows, and a lot of specific syntax which are databricks-specific and not spark in general. **What problems is Azure Databricks solving and how is that benefiting you?** I have written code to ingest data, and perform analytics over the same. It has benefitted the business to analyse their dataset. ### 43. Azure Databricks Review **Rating:** 5.0/5.0 stars **Reviewed by:** Raina S. | Associate Software Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** October 26, 2023 **What do you like best about Azure Databricks?** I'm liking all the feature of azure databricks specially coding facilities. We can do the coding in Scala, pyspark and using R language. Also the best part it it we can make use of Sql, to query. I used to code in databricks using pyspark and sql features and with this I can do entire ETL process( Exrract, transform and load the data into database). **What do you dislike about Azure Databricks?** There is nothing as such which I don't like about azure databricks, only sometimes the drivers are becoming unhealthy due to heavy load on cluster and sometimes to clear ka cache we need to restart the cluster. **What problems is Azure Databricks solving and how is that benefiting you?** Azure is helping me to connect with the containers as well as connecting with the database to quickly and easily read the data and apply the transformations logic in it. ### 44. Best tool for big data handling **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Small-Business (50 or fewer emp.) **Reviewed Date:** December 17, 2023 **What do you like best about Azure Databricks?** I am a data engineer and Databricks integration into azure has made my work a lot easier i can directly spin up spark clusters on cloud and work on big data .The interface is easy to use just like a python notebook and its packed with so many features. **What do you dislike about Azure Databricks?** well for me there hasn't been any issues while using but using azure databricks can cost money. You need to be careful about how much you use to avoid high bills.azure databricks works closely with microsoft azure. If you prefer using different cloud services his might not be the best for you. **What problems is Azure Databricks solving and how is that benefiting you?** As a data engineer i work on big data ,so azure databricks allows me to just spin up a cluster and write spark code in jupyter notebook like setup and all my data is already accesible ia azure storage services. ### 45. Easy to handle Big Data transformations **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Consulting | Enterprise (> 1000 emp.) **Reviewed Date:** November 02, 2023 **What do you like best about Azure Databricks?** It has a fexcibility to handle big data and databricks provides functionallity of delta lake so it's easy to read and write data in parquet format that is more faster in processing also delta lake is more usable as deta lake. **What do you dislike about Azure Databricks?** No dislike yet, Only thing is that it gives the performance as per Cluster level configuration. So some times it takes higher cost or processing. **What problems is Azure Databricks solving and how is that benefiting you?** Azure databricks addresses the challenge of couples big data analytics by providing a collaborative , integrated platform of data processing. It also supports multiple languages like pyspark, Scala and spark sql that gives benifit to do transformations in one notebook. Also it benifiting by accelerating data-driven insights, enhancing productivity, and enabling more informed, data-backed decision-making, leading to better business outcomes. ### 46. Good solution for data management with pain of indexing data **Rating:** 4.0/5.0 stars **Reviewed by:** Mitul S. | Technical Lead, Enterprise (> 1000 emp.) **Reviewed Date:** September 12, 2023 **What do you like best about Azure Databricks?** One of the best datalake solutions in the market with efficient data storage and retrieval capabilities. Also introduction of various layers like bronze, silve and Gold allows you to segregate your logical data retrieval **What do you dislike about Azure Databricks?** One of the major drawbacks is integration with third party tools if someone wants to connect to azure Databricks with HL7 spy or Caristix. Also UI needs some modifications in terms of how much data one can allow to be populated from cache **What problems is Azure Databricks solving and how is that benefiting you?** Serves as datalakehouse solution for storing raw data as well as transformed and translated data that can be used as database for observability tools and periodic data health check ### 47. Azure Databricks review **Rating:** 4.5/5.0 stars **Reviewed by:** Dhiraj M. | Senior Data Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** July 06, 2023 **What do you like best about Azure Databricks?** Azure Databricks is a very powerful ETL tool integrated with Spark. We can use python, scala , java and sql language to write our ETL logic and then it has its own inhouse hive storage and also it can perform orchestration. **What do you dislike about Azure Databricks?** The main disadvantage which I think its relational database model. Which is not powerful as other rdbms but they are working on it using delta and iceberg concept. **What problems is Azure Databricks solving and how is that benefiting you?** Azure Databricks is a powerful ETL tool integrated with Spark. We can use python, scala , java and sql language to write our ETL logic and then it has its own inhouse hive storage and also it can perform orchestration. We mainly using it for writing conplext ETL transformations to cater business requirements. ### 48. Cloud based spark for big data analytics and AI **Rating:** 4.5/5.0 stars **Reviewed by:** Gaurang S. | Assistant Manager DevOps, Enterprise (> 1000 emp.) **Reviewed Date:** October 11, 2023 **What do you like best about Azure Databricks?** -Spinning up cloud based Spark environmet in minutes , autoscale capabilities in case of high performance required. -Multi language support like python, Scala , R , Java , SQL - Best tool for AI based systems and data science requirements. -large scale data processing for both batch & streaming workloads. **What do you dislike about Azure Databricks?** There are no downsides of Azure databricks as it's having many benefits like large scale data processing for both batch & streaming workloads. End to end data analytics. So featurewise there are no drawback at all **What problems is Azure Databricks solving and how is that benefiting you?** large scale data processing for both batch & streaming workloads. -Easy integration with Azure devops pipelines , GitHub - Collaboration using shared workspace - Improved Capex ### 49. Azure Databricks in Production **Rating:** 3.5/5.0 stars **Reviewed by:** Parag P. | Lead Data Scientist, Enterprise (> 1000 emp.) **Reviewed Date:** October 21, 2023 **What do you like best about Azure Databricks?** Azure databricks is easy to use and support all the features like data engineering tools support like spark and mlops tools like mlflow. Easy to scale in production with minimal efforts **What do you dislike about Azure Databricks?** Few components are tightly coupled those are not flexible to change **What problems is Azure Databricks solving and how is that benefiting you?** We have huge amount of data which is difficult to manage in traditional machine learning framework. Azure databricks provides support of spark using that we can easily manage our data pipeline also it does support mlops with native support of mlflow using this we are able to manage entire machine learning cycle. ### 50. Ignite the spark in you **Rating:** 5.0/5.0 stars **Reviewed by:** Avinash K. | Resident Solutions Consultant, Enterprise (> 1000 emp.) **Reviewed Date:** April 16, 2020 **What do you like best about Azure Databricks?** Readily available infrastructure with realtime help and ample examples to develop logic. Easy infrastructure creation and maintenance. Configurable to almost all data sources. **What do you dislike about Azure Databricks?** Less choice on configuration of clusters **Recommendations to others considering Azure Databricks:** If you want to leave behind the day to day pain of managing infrastructure and just focus on development and coding then databricks is the best option **What problems is Azure Databricks solving and how is that benefiting you?** I have used databricks to extract and transform social networking data in real time and process it. The notebooks simply the operation. Full support of python. Running parallel jobs and integration with webhooks. ## Azure Databricks Discussions - [When data is small how can I reconfigure cluster to automatically adjust . I don't know which day data coming will be small.](https://www.g2.com/discussions/azure-databricks-when-data-is-small-how-can-i-reconfigure-cluster-to-automatically-adjust-i-don-t-know-which-day-dat) - 1 comment, 1 upvote - [What is the best way to databricks in ADF](https://www.g2.com/discussions/26515-what-is-the-best-way-to-databricks-in-adf) - 1 comment, 1 upvote - [What is Azure Databricks used for?](https://www.g2.com/discussions/azure-databricks-what-is-azure-databricks-used-for) - 1 comment - [Is Azure Databricks PaaS or SAAS?](https://www.g2.com/discussions/is-azure-databricks-paas-or-saas) - 2 comments - [Does Microsoft own Databricks?](https://www.g2.com/discussions/does-microsoft-own-databricks) - 2 comments - [View Azure Databricks pricing details and edition comparison](https://www.g2.com/products/azure-databricks/reviews?section=pricing&secure%5Bexpires_at%5D=2026-05-31+14%3A15%3A19+-0500&secure%5Bsession_id%5D=b92204c0-9ffe-4352-bf5a-0ea05aa65b0d&secure%5Btoken%5D=05d7a6dc773b82f6b4df01d27710ffd47dbeeff6d156226ecd782ef883a0bdaa&format=llm_user) ## Azure Databricks Integrations - [Azure Cosmos DB](https://www.g2.com/products/azure-cosmos-db/reviews) - [Azure Data Factory](https://www.g2.com/products/azure-data-factory/reviews) - [Azure Data Lake Store](https://www.g2.com/products/azure-data-lake-store/reviews) - [Azure Synapse Analytics](https://www.g2.com/products/azure-synapse-analytics/reviews) - [GitHub](https://www.g2.com/products/github/reviews) - [GitLab](https://www.g2.com/products/gitlab/reviews) - [Microsoft Power BI](https://www.g2.com/products/microsoft-microsoft-power-bi/reviews) ## Azure Databricks Features **Data Transformation** - Real-Time Analytics - Data Querying **Connectivity** - Hadoop Integration - Spark Integration - Multi-Source Analysis - Data Lake **Operations** - Data Visualization - Data Workflow - Governed Discovery - Embedded Analytics - Notebooks **Building Reports** - Data Transformation - Data Modeling - WYSIWYG Report Design - Integration APIs **Platform** - Mobile User Support - Customization - User, Role, and Access Management - Internationalization - Sandbox / Test Environments - Performance and Reliability - Breadth of Partner Applications ## Top Azure Databricks Alternatives - [Alteryx](https://www.g2.com/products/alteryx/reviews) - 4.6/5.0 (774 reviews) - [Snowflake](https://www.g2.com/products/snowflake/reviews) - 4.6/5.0 (705 reviews) - [Splunk Enterprise](https://www.g2.com/products/splunk-enterprise/reviews) - 4.3/5.0 (414 reviews)