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216 Azure Databricks Reviews
Overall Review Sentiment for Azure Databricks
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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. Review collected by and hosted on G2.com.
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. Review collected by and hosted on G2.com.
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. Review collected by and hosted on G2.com.
Sometime pricing structure create problem for small business.
Starting cluster with high dataset take more time to get started. Review collected by and hosted on G2.com.
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. Review collected by and hosted on G2.com.
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. Review collected by and hosted on G2.com.
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Easy to write programs a d executes all scripts , user friendly application Review collected by and hosted on G2.com.
Everything ok it was updating day by day making every user free and stress less tool Review collected by and hosted on G2.com.
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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. Review collected by and hosted on G2.com.
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. Review collected by and hosted on G2.com.
Its big data processing capablity and multiple language interface in one notebook Review collected by and hosted on G2.com.
Workflows monitoring and ui is not mature enough to handle multiple pipeline exceution Review collected by and hosted on G2.com.
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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. Review collected by and hosted on G2.com.
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." Review collected by and hosted on G2.com.
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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 . Review collected by and hosted on G2.com.
As such nothing I only feel one drawback is thst they are not having there own storage Review collected by and hosted on G2.com.
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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. Review collected by and hosted on G2.com.
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. Review collected by and hosted on G2.com.