Databricks Data Intelligence Platform Pricing Overview

its seamless integration of data engineering, data science, and machine learning workflows in one unified platform. It enhances collaboration, accelerates data processing, and provides scalable solutions for complex analytics, all while maintaining a user-friendly interface. Review collected by and hosted on G2.com.

Another drawback is the limitation with RDDs and the lack of support for ML Runtime in the standard compute tier.

The pricing model, which can become expensive as usage scales, especially for smaller teams or projects. Review collected by and hosted on G2.com.

The platform itself is relatively easy to use and quick to stand up. Initial setup was straightforward, and core workflows were accessible without excessive configuration. From a purely technical standpoint, the product is usable and well-designed. Review collected by and hosted on G2.com.

Databricks needs to take real accountability for pricing accuracy and post-sale remediation. Their usage and pricing calculator was materially wrong for our use case (off by ~10x), and we raised concerns early. We never received the level of attention or corrective action needed to resolve it properly.

We ended up paying more than 10x the expected cost, with only the final quarter partially rebated, which is not a meaningful remedy. Databricks declined responsibility and instead referenced emails sent after the contract was signed, which did not align with when the issue was identified.

This experience has made us seriously reconsider alternatives like Snowflake. My advice to others: be extremely cautious with Databricks’ pricing estimates and assume you will bear the risk if they are wrong. Once the contract is signed, resolution is difficult, and revenue protection appears to take priority over customer outcomes. Review collected by and hosted on G2.com.