# Azure Databricks Reviews 2026. Verified Reviews, Pros & Cons | Capterra > Is Azure Databricks the right Machine Learning solution for you? Explore 10 verified user reviews from people in industries like yours to make a confident choice. Source: https://www.capterra.com/p/246719/Azure-Databricks/reviews --- Azure Databricks 4.7 (10) Provider data verified by our Software Research team, and reviews moderated by our Reviews Verification team. [Learn more](https://www.capterra.com/our-story/) * * * Last updated March 15th, 2026 # Reviews of Azure Databricks Ease of use 4.7 Customer Service 4.5 ## Showing most helpful reviews Showing 1-10 of 10 Reviews Sort by: Most Helpful Rating Company Size Reviewer's Role Length of Use Frequency of Use Wealth A. Data Engineer Financial Services Used the software for: 6-12 months ### "High-Performance Analytics for Modern Data Teams" March 31, 2026 5.0 Azure Databricks provides a robust platform for big data analytics and machine learning. Its performance and scalability make it ideal for enterprise-level data processing, and the integration with Azure services streamlines workflows. While it may feel complex initially, the productivity gains and flexibility it offers make it worth adopting. Pros Seamless integration with Azure ecosystem and other cloud services. Excellent performance and speed for large-scale data processing. Flexible environment for both data engineering and data science workloads. Strong support for Spark-based analytics and collaborative workflows. Cons Steeper learning curve for beginners without Spark experience. Pricing can be high for smaller teams or experimental projects. Some advanced features require additional configuration or expertise. Switched from [Azure Synapse Analytics](https://www.capterra.com/p/170434/SQL-Data-Warehouse/) Cost implications were alarming and not suitable Review Source SA Samuel A. Software Telecommunications Used the software for: I used a free trial ### "Harnessing Data Powerhouse with Azure Databricks" May 18, 2023 5.0 A powerful data processing and analytics solution offering comprehensive machine learning capabilities. Pros Masterclass in Machine Learning Capabilities, Big Data Analytics, and Seamless Azure Integration with Admirable Speed and Efficiency. Cons Falls short in language versatility and default storage capacity; requires a learning curve and strategic planning for potential data overload. Switched from [Microsoft SQL Server](https://www.capterra.com/p/1417/SQL-Server/)[Google Cloud](https://www.capterra.com/p/268690/Google-Cloud-Platform/) While Google Cloud has robust services, Azure Databricks offers more seamless integration with other Microsoft products Review Source PG Pranshu G. Assciate Data Engineer Information Technology and Services Used the software for: 1-2 years ### "Azure databricks : Not just a Paas tool" January 19, 2024 4.0 Pros What I have come to love most about this tool is runs on most popular and best in class spark environment. The most sincere availability of cloud infrastructure is undoubtedly a big concern when you are dealing with multi node/cluster distributed programming. It also supports multi language supporting scala, pyspark, spark sql. Super useful. Cons All things said, there are still few areas where azure databricks can improve upon. For instance, the pipeline orchestration is still pretty primitive as compared to its competitors. They are lacking most of most common features. Review Source VR Verified Reviewer Developer Information Technology and Services Used the software for: 1-2 years ### "Prons & Cons of Azure Databricks" January 9, 2026 5.0 Overall, Azure Databricks is great platform for data ingesting, processing and dashboarding with highly optmized engines and supports for various inbuild features. Pros Azure Databricks supporrs for different language like SQl, Python, and, Java etc. Its easy to use for new beginners and supports for git and devops integration make it more flexible to work in big projects. Azure Databricks supports for reporting and machine learning make it compatible amd unified platform where all developers, analyst, and data scientists can work at same platform therefore reducing cost. Cons Azure Databricks processing engine habe some bugs like null value if timestamp column provided as other data type column. So its need to be fixed. Azure Databricks high cost for dashboarding and ingesting data from cloud and on premises data. Review Source Tej P. DevOps Engineer Information Technology and Services Used the software for: 1-2 years ### "Databricks for data world" April 13, 2024 5.0 It provides simplifies the data journey by providing a single solution for data engineering, analytics, and machine learning. It Handles large datasets effortlessly for data processing and analysis tasks. It provides integration with other tools for data preparation, real-time processing, and advanced analytics. It provides scalability, cost-efficiency, and robust security features to ensure that businesses can manage their data with compliance and regulation. Pros It provides some key features like workspace, notebook, Apache spark, Delta Lake, and Scalability. It provides a centralized environment where teams can collaborate. We can work on Jupyter Notebook with Apache Spark which provides the engine that powers all processing of dataset. It provides Cross-team collaboration so engineers, analysts, scientists, and ML engineers can work seamlessly on the same platform. It also provides consistency with notebooks, users can transition between tasks and programming languages without the need for context-switching. Cons In this Databricks platform, we can't migrate a library from the dev workspace to the prod workspace. Review Source Shaunak P. Data Platform Engineer Information Technology and Services Used the software for: 1-2 years ### "Single workspace for all your analytics, code editing and transformation needs!" January 20, 2023 5.0 Azure Databrick is very easy to learn, and they provide a lot of certifications. Their community is huge. It does its work well. We majorly leverage our work on Interactive Notebooks on Databricks. Pros There are a lot of pros, as Azure Databricks is huge SaaS product offering.Instead of mentioning about what Azure Databricks does, I will just focus this section on pros (which you may not get anywhere else)1) Delta Lake, Apache Spark, Redash, etc. are open-source projects that are maintained and founded by Databricks team of engineers.2) Top notch and highly available services like Workflows and Photon.3) They will not force you to migrate application data to their proprietary storage systems, you can configure it on cloud for you.5) They provide a flagship service called Unity Catalogue, it helps you to manage the permission within databricks on azure.6) You can use Azure Databricks not only via UI but also Rest API, CLI & Terraform. Cons There are a lot of features and guides but when it comes to deployment of new features or version upgrade, Azure Databricks team does not provide any intimation. These creates reverse dependency issues for stable pipelines in PROD. However, we cannot obstruct the new changes coming in, but can at least try to comply with the critical changes. Also, there are a lot of outages in certain regions. Alternatives considered [Azure Synapse Analytics](https://www.capterra.com/p/170434/SQL-Data-Warehouse/) Review Source VR Verified Reviewer Software Engineer 2 Information Technology and Services Used the software for: 1-2 years ### "Best solution for Big Data Analytics with Spark" February 24, 2023 5.0 Pros I like working in Azure Databricks a lot. The thing that I like the most about it is its integration with Azure: Databricks is tightly integrated with Azure, which makes it easy to set up and use within the Azure ecosystem. It allows you to access data from Azure Data Lake Storage, Azure Blob Storage, and other Azure services and also integrates with Azure Machine Learning. Cons Azure Databricks is great but, when it comes to cost, Databricks can be expensive, particularly for large-scale data processing tasks. The cost can quickly add up as you increase the number of nodes and storage capacity. Review Source AM Amr M. Instructional Designer. Higher Education Used the software for: 1-2 years ### "Seamless Data Service on Microsoft Azure" May 9, 2022 4.0 As a member of the data analytics team, I find Microsoft Azure Databricks efficient and allows my team to integrate Databricks SQL with Power BI to build advanced data analysis solutions that process big datasets. Also, we use the Databricks Machine Learning service to run training models on our data sets related to students learning records. It helps us build better data analysis solutions, improve the design and delivery of our online courses, and build/embed more impactful recommendation systems into learning management systems. Pros Azure Databricks is easy to use, quick to start with and works seamlessly with Azure data services like Azure Data Lake Storage. It facilitates the big-data Analytics workload optimization and connects seamlessly with Power BI. The service documentation is well-organized and easy to follow to make it easy for non-data scientists to build advanced data analytics pipelines with basic programming skills. Cons Azure Databricks Service requires experience with the Azure platform, and new users might easily get lost. Also, it is not as seamless with applications outside the Microsoft environment. Alternatives considered [Google Cloud](https://www.capterra.com/p/268690/Google-Cloud-Platform/) Review Source Charles B. Data engineer Information Technology and Services Used the software for: 1-2 years ### "Data Engineering very fast" January 13, 2023 4.0 Pros The Azure portal offers an easy path to this tool. Its supports access by keyvault. Cons The variables switched between data factory and databricks are not get by a simple way. Review Source VR Verified Reviewer Engineer Information Technology and Services Used the software for: 6-12 months ### "コードを実行するノートブックとデータレイクが統合されているので使いやすい！" December 27, 2022 5.0 Pros データレイクのデータ一覧と、コードを実行するＰｙｔｈｏｎノートブックが同一の画面に出てくるので、画面の行ったり来たりが無く使いやすい。また、ｓｐａｒｋテーブルのまま保存することができるので、クエリの実行結果が返ってくるのが非常に早い。さらに、他のＭＳ製品ともシームレスに繋ぐことができ、作業負荷が小さい。 Cons 強いて言うならば、データレイクなので、テーブルの命名規則を事前に設定・整備しておかないと、テーブルの一覧が煩雑になってしまうことでしょうか。 Reason for choosing Azure Databricks スパークテーブルのままデータを保持でき、クエリが高速なため。 Review Source Similar Products Featured ## Related categories [Machine Learning](https://www.capterra.com/machine-learning-software/)