# Platform comparisons

> Databricks compared with Snowflake, Microsoft Fabric, BigQuery, Redshift and Palantir Foundry, and Temporal with Airflow. Every fact links to the vendor's own page and the day it was read. Written by TechFabric, a Databricks partner.

Canonical: https://www.techfabric.com/compare

- [Databricks vs BigQuery](https://www.techfabric.com/compare/databricks-vs-bigquery): If your data and teams live in Google Cloud and the work is mostly SQL analytics and BI, BigQuery is the simpler choice. There are no clusters to run, you pay per query or per slot, and Gemini is built into the console. Choose Databricks when heavy Spark or Python engineering, custom ML and AI agents, or a platform that also runs on AWS and Azure matter more.
- [Databricks vs Palantir Foundry](https://www.techfabric.com/compare/databricks-vs-palantir): Choose Databricks if your team wants to engineer data, analytics and AI itself on open formats, pay by usage, and keep the platform in your own cloud. Choose Foundry if you want a packaged operational layer, the Ontology, for frontline apps and decisions, or need air-gapped or classified deployment. Databricks says more than 100 customers run both, and the two vendors have had a product partnership since March 2025.
- [Databricks vs Redshift](https://www.techfabric.com/compare/databricks-vs-redshift): If you're all-in on AWS, the work is SQL reporting and dashboards, and your sources are Aurora, RDS, DynamoDB or SaaS apps that zero-ETL integrations can replicate, Redshift is the shorter path. Choose Databricks when data engineering, streaming, ML and AI agents matter as much as BI, or when you need the same platform outside AWS.
- [Microsoft Fabric vs Databricks](https://www.techfabric.com/compare/microsoft-fabric-vs-databricks): Choose Fabric if you are a Microsoft and Power BI organization that wants one SaaS product, one capacity bill and mostly SQL, reporting and low-code pipelines. Choose Databricks if you run heavy engineering, ML or agent workloads, need more than one cloud, or want fine control of compute. The two also connect, since Fabric can mirror Unity Catalog tables without copying them.
- [Snowflake vs Databricks](https://www.techfabric.com/compare/snowflake-vs-databricks): Choose Snowflake if most of your work is SQL analytics and you want a managed warehouse that a small team can run. Choose Databricks if you also do heavy data engineering, streaming, machine learning or agents on the same data, or want your tables in open formats in your own cloud account. Both now read and write Iceberg, so running both is realistic.
- [Temporal vs Airflow](https://www.techfabric.com/compare/temporal-vs-airflow): Pick Airflow for scheduled batch data pipelines. It has a long list of provider packages, asset-aware scheduling, lineage through OpenLineage, and several managed services. Pick Temporal when the workflow is application logic, such as orders, payments, provisioning or AI agents. It suits work that must survive failures, wait for signals or people, run for days or years, or be written in languages other than Python.