Amazon Redshift vs Databricks

Updated November 2026 · AppBreakup editorial

Amazon Redshift

AWS's managed cloud data warehouse, available as provisioned clusters or a serverless option.

Paid

Visit Amazon Redshift Amazon Redshift profile

Databricks

A lakehouse platform combining data engineering, SQL warehousing and machine learning on your cloud.

Paid

Visit Databricks Databricks profile

The short answer

Amazon Redshift is AWS's managed SQL data warehouse, best for teams already on AWS that want analytics tied into IAM, S3 and other AWS services. Databricks is a lakehouse platform for data engineering, SQL and machine learning that runs on AWS, Azure and Google Cloud. Pick Redshift for SQL analytics inside AWS; pick Databricks for Spark, ML and multi-cloud work on open formats.

Amazon Redshift or Databricks: our take

Redshift is a classic cloud data warehouse. It stores data in columns across nodes so large SQL queries run in parallel, speaks a PostgreSQL-flavoured dialect that common BI tools support, and comes as provisioned clusters you size yourself or as Redshift Serverless. Spectrum queries files in S3 directly, and zero-ETL integrations replicate data from AWS databases. Databricks takes a lakehouse approach: data stays in open formats such as Delta Lake and Parquet in your own cloud storage, and Databricks supplies the compute and tools on top, including Spark-based data engineering, Databricks SQL warehouses, collaborative notebooks, MLflow and Unity Catalog for governance.

Cloud choice is often decisive. Redshift runs only on AWS, and its deep integration with IAM, Lake Formation, QuickSight and SageMaker is the main reason AWS-centred teams pick it. Databricks runs on AWS, Azure and Google Cloud, which suits multi-cloud organisations or teams that want to avoid being tied to one provider's warehouse.

Both bill by usage, and both can be hard to forecast. Redshift provisioned clusters start at $0.543 per hour, Serverless starts from $1.50 per hour, billing is per second with a 60-second minimum, and new Serverless users get a $300 credit for 90 days. Databricks is pay as you go with no up-front cost, measured in Databricks Units (DBUs), and on most clouds the underlying virtual machines are billed separately by your cloud provider. A free trial is available.

Redshift is the simpler choice when the job is SQL analytics and dashboards on AWS, though provisioned clusters need sizing and tuning. Databricks is more of a platform to learn and can be overkill for teams that only need BI, but it fits data engineering and data science teams that want ETL, SQL and model training in one place.

Choose Amazon Redshift if…

Teams on AWS that want a managed SQL warehouse integrated with their other AWS services
Serverless option bills compute per second
Queries data in S3 directly with Spectrum

Choose Databricks if…

Data engineering and ML teams that want SQL, Spark and model training on one platform
Data stays in open formats in your own cloud storage
Covers ETL, SQL analytics and machine learning in one place

What is Amazon Redshift?

Amazon Redshift is the data warehouse service from Amazon Web Services. It stores data in columns across many nodes so large SQL analytics queries run in parallel, and it speaks a PostgreSQL-flavoured dialect that most BI tools connect to. You can run it as provisioned clusters you size yourself, or as Redshift Serverless, which bills for compute by the second while it runs queries. Redshift Spectrum queries files sitting in S3, including open table formats, without loading them first, and zero-ETL integrations replicate data from AWS databases. It also ties into IAM, Lake Formation, QuickSight and SageMaker, which is the main reason AWS-centred teams choose it. It suits companies already on AWS that want SQL analytics at scale without leaving that ecosystem. It is paid, with usage-based pricing and a credit-based trial for Serverless; costs can be harder to predict than flat plans, and it runs only on AWS, so multi-cloud teams often prefer Snowflake or Databricks.

What is Databricks?

Databricks is a data and AI platform built around the lakehouse idea: data stays in open formats such as Delta Lake and Parquet in your own cloud storage, and Databricks provides the compute and tools on top. It was founded by the creators of Apache Spark, and Spark-based data engineering remains its core, alongside Databricks SQL warehouses for BI, collaborative notebooks, MLflow for machine learning, and Unity Catalog for governance. It runs on AWS, Azure and Google Cloud, and is aimed at data engineering and data science teams in mid-sized and large organisations. Pricing is pay-as-you-go in Databricks Units (DBUs), a normalised measure of processing, and on most clouds you also pay the cloud provider separately for the underlying virtual machines. A free trial is available. It is more of a platform to learn than a plain SQL warehouse, which makes it heavier than needed for teams that only want dashboards.

Side by side

Attribute	Amazon Redshift	Databricks
Pricing	Paid	Paid
Open source	No	No
Self-hostable	No	No
Platforms	Web	Web
Best for	Teams on AWS that want a managed SQL warehouse integrated with their other AWS services	Data engineering and ML teams that want SQL, Spark and model training on one platform
Status	Active	Active

Verified facts, compared

Facts both apps publish, checked on each vendor's own site.

Fact	Amazon Redshift	Databricks
Free trial	$300 credit for 90 days	Yes