Top Rated Azure Databricks Alternatives
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Delta Processing using Azure Databricks & Azure Data Factory
216 Azure Databricks Reviews
Overall Review Sentiment for Azure Databricks
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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. Review collected by and hosted on G2.com.
Only thing is its very costly, so need to constantly monitor resource usage. Review collected by and hosted on G2.com.
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 Review collected by and hosted on G2.com.
So far I have not found anything to dislike. Azure Databricks is definately a plus to both Databricks and Azure users Review collected by and hosted on G2.com.
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. Review collected by and hosted on G2.com.
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. Review collected by and hosted on G2.com.
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. Review collected by and hosted on G2.com.
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. Review collected by and hosted on G2.com.
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 Review collected by and hosted on G2.com.
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. Review collected by and hosted on G2.com.
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. Review collected by and hosted on G2.com.
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. Review collected by and hosted on G2.com.
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. Review collected by and hosted on G2.com.
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. Review collected by and hosted on G2.com.
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 Review collected by and hosted on G2.com.
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 Review collected by and hosted on G2.com.
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. Review collected by and hosted on G2.com.
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. Review collected by and hosted on G2.com.
