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.

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.

It's designed for engineers! Makes accessing cloud cluster so convenient! Review collected by and hosted on G2.com.

It's hard to understand full cost at times. Review collected by and hosted on G2.com.

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.

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.