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SlateIndex
Amazon RedshiftFully managed, petabyte-scale cloud data warehouse on AWS
vs
DatabricksUnified data, analytics and AI platform on an open lakehouse
Comparison · Data Warehouse · weekly run Nov 3

Amazon Redshift vs Databricks

Which one do AI engines recommend, and how do they differ on price, fit and features?

The short answer

Amazon Redshift is the stronger AI pick in Data Warehouse: it has a visibility score of 40.5 versus 37.9 for Databricks, and ranks ahead in 56% of the answers that name both.

Choose Amazon Redshift if…

  • You want the brand AI engines rank higher (40.5 vs 37.9)
  • You need ISO 9001 or C5 or PCI DSS or SOC 2 coverage
  • Petabyte-scale, fully managed data warehouse service
  • Deep integration with AWS services like S3, IAM, and existing AWS operations

Choose Databricks if…

  • AI answers describe it more positively (35% vs 19% positive)
  • You need ISO 27701 or SOC 2 Type II or SOC 3 coverage
  • Lakehouse architecture combining data warehousing with data lake flexibility
  • Strong for machine learning, AI, and data engineering workloads

AI visibility side by side

Latest weekly run · Nov 3

Metric Amazon Redshift Databricks
Visibility score40.5%37.9%
Change vs last weekNewNew
Rank in Data Warehouse#3#4
Share of voice9.8%9.3%
Mentions this run5552
Positive in AI answers19%35%

The stronger value in each row is marked with a ✓.

Visibility score trend

Weekly runs over the last 60 days

0%25%50%75%100%Nov 3Amazon Redshift 41%

Amazon Redshift 0pp · Databricks 0pp over 0 weekly runs.

Engine by engine

Amazon Redshift leads on 2 of 3 engines

ChatGPT
47%
46.1%
AI Mode
32%
35.4%
Perplexity
42.4%
32.2%
Amazon RedshiftDatabricks

Head to head in AI answers

45 engine answers name both brands

25Amazon Redshift ranked higher
20Databricks ranked higher

Features, pricing & fit

DimensionAmazon RedshiftDatabricks
DeploymentCloud, fully managed on AWS, as Provisioned clusters or ServerlessAvailable across all major cloud providers
ComplianceISO 27001, ISO 27017, ISO 27018, ISO 9001, C5, PCI DSS, SOC 1, SOC 2ISO 27001, ISO 27017, ISO 27018, ISO 27701, SOC 1, SOC 2 Type II, SOC 3
Support—Technical support on request, Technical documentation
Founded20132013
Headquarters—San Francisco, CA
Employees—5,000+
Funding—Round at $60B valuation, including secondary sale
Best for—Data engineering, data science, analytics and AI teams at startups and global enterprises

Pros and cons

Themes from the AI answers that mention each brand

Amazon Redshift

  • Petabyte-scale, fully managed data warehouse service
  • Deep integration with AWS services like S3, IAM, and existing AWS operations
  • Reserved pricing can cut compute costs substantially for committed use
  • Free trial with Redshift Serverless or node-hour allowance
  • Widely shortlisted as a leading cloud data warehouse
  • Requires capacity and cost management, and bills can be hard to predict

Databricks

  • Lakehouse architecture combining data warehousing with data lake flexibility
  • Strong for machine learning, AI, and data engineering workloads
  • Top customer satisfaction ratings alongside Snowflake
  • Free trial and free Edition for learning
  • Discounts for annual prepaid commitments
  • Complex consumption-based pricing with no single fixed price
  • Best only when ML, Spark, or Python skills are central to the team

Data collected ·ChatGPT, Perplexity, Google AI Mode·coverage 100%·next run

Cite as: SlateIndex, “Amazon Redshift vs Databricks”, https://slateindex.ai/compare/amazon-redshift-vs-databricks, data of Nov 3, 2026. Licence: CC BY 4.0.