unified data analytics
March 06, 2026

unified data analytics

Raghwendra Singh | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User

Overall Satisfaction with Databricks Data Intelligence Platform

Databricks is used to run all the data engineering, data science, analytics jobs related to spark , feature engineering jobs of data science and all the model training jobs of datascience. Databricks SQLwarehouse is also used as the main compute for serving the analytics powering the queries between 10 minutes to 60 minutes

Pros

  • Databricks provides an amazing notebook which serves and the backbone of unified analytics for all things data engineering, data science, and analytics
  • the performance of Databricks SQL Warehouse is top notch and very hard to beat by many competitors , and amazing performance optimization for delta file format
  • Databricks' support for iceberg format is also very good allowing for no vendor lock - in for delta format

Cons

  • The Unity catalog is restrictive in terms of policy definition due to user-defined functions compared to market alternatives like Apache Ranger or Open Policy Agent.
  • Unity Catalog has a table quota limitation where a schema with a higher number of tables requires increasing the table quota repeatedly , which is not an issue if you use Hive Metastore.
  • SQL Warehouse as a solution is amazing and performant, but there should have been some support to add Spark plugins or extensions so that there is some room for changes or adding custom dependencies
  • the SLA has reduced due to the performance improvement when we migrated from oss spark to Databricks.
  • the notebook is very well polished with lots of features , boosting our analyst productivity
  • The Databricks workflows are a powerful tool to create complex dependency graphs and dags in one place
its a platform which can be used by teams with less data expertise to very large teams with high data expertise . It offers a wide variety of features for different computer types suited for interactive notebooks, jobs , and SQL warehouses. The MLOps functionalities also being present making Databricks a go-to choice for data science teams
Databricks notebook give a good managed solution to all of these solutions combined with minimal maintenance

Do you think Databricks Data Intelligence Platform delivers good value for the price?

Yes

Are you happy with Databricks Data Intelligence Platform's feature set?

Yes

Did Databricks Data Intelligence Platform live up to sales and marketing promises?

Yes

Did implementation of Databricks Data Intelligence Platform go as expected?

Yes

Would you buy Databricks Data Intelligence Platform again?

Yes

for a new team with less number of users Databricks outshines due to the unified analytics , and provided all solutions from data ingestion to data lake ETL , to data consumption with a modern notebook . The Databricks GPU and Spark runtimes are also very well maintained and are regularly updated. So there is very little maintenance. If someone is using Databricks but does not use Unity Catalog, then they miss out on a lot of advanced features like SQL Warehouse serverless. Making Unity Catalog optional would have been easier for non-Unity Catalog customers to use the full capabilities of Databricks and the newer features that require Unity Catalog

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