Azure Databricks Reviews & Product Details

This is the best implementation of Databricks I could have hoped for. Review collected by and hosted on G2.com.

Occasionally, when I put my laptop to sleep, my Azure Databricks sessions do not reconnect quickly. Review collected by and hosted on G2.com.

Huge data celan transfer. And this is mainly use from banking Review collected by and hosted on G2.com.

This is the complex setup . Do not optimisation Review collected by and hosted on G2.com.

Its like a one stop shop for everything. Review collected by and hosted on G2.com.

Sometimes the use of python with sql gets complicated. Review collected by and hosted on G2.com.

They are improving the existing features and adding new features for easy integration. Review collected by and hosted on G2.com.

Some features are not very intuitive and user friendly live crearting secret scope. Review collected by and hosted on G2.com.

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.

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. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

Unified data eco system capability for DE and ML Review collected by and hosted on G2.com.

Steep learning curve, still evolving on basics 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.

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.