DatabricksUnified data, analytics and AI platform on an open lakehouse
vs
OpenSearchThe open engine for AI-powered search and observability
Comparison · Vector Databases · weekly run Nov 2
Databricks vs OpenSearch
Which one do AI engines recommend, and how do they differ on price, fit and features?
The short answer
OpenSearch is the stronger AI pick in Vector Databases: it has a visibility score of 3.9 versus 1.4 for Databricks.
Choose Databricks if…
- AI answers describe it more positively (35% vs 0% positive)
- You need ISO 27001 or ISO 27017 or ISO 27018 or ISO 27701 or SOC 1 or SOC 2 Type II or SOC 3 coverage
- You prefer a larger, established vendor (5,000+ employees)
- Lakehouse architecture combining data warehousing with data lake flexibility
Choose OpenSearch if…
- You want the brand AI engines rank higher (3.9 vs 1.4)
- Strong general database popularity
- Hybrid keyword-plus-semantic search with dense vectors
- Suited to broader search, logging, analytics, and observability
AI visibility side by side
Latest weekly run · Nov 2
| Metric | Databricks | OpenSearch |
|---|---|---|
| Visibility score | 1.4% | 3.9% |
| Change vs last week | New | New |
| Rank in Vector Databases | #22 | #16 |
| Share of voice | 0.8% | 1.7% |
| Mentions this run | 4 | 8 |
| Positive in AI answers | 35% | 0% |
The stronger value in each row is marked with a ✓.
Visibility score trend
Weekly runs over the last 60 days
Databricks 0pp · OpenSearch 0pp over 0 weekly runs.
Engine by engine
OpenSearch leads on 3 of 3 engines
ChatGPT
AI Mode
Perplexity
DatabricksOpenSearch
Head to head in AI answers
0 engine answers name both brands
0Databricks ranked higher
0OpenSearch ranked higher
Features, pricing & fit
| Dimension | Databricks | OpenSearch |
|---|---|---|
| Deployment | Available across all major cloud providers | Self-managed, or through Amazon OpenSearch Service and managed providers such as Aiven and Instaclustr. A Kubernetes operator is available for managing clusters. |
| Compliance | ISO 27001, ISO 27017, ISO 27018, ISO 27701, SOC 1, SOC 2 Type II, SOC 3 | — |
| Support | Technical support on request, Technical documentation | Community forum, Slack, GitHub, Long-term support from certified providers |
| Founded | 2013 | 2021 |
| Headquarters | San Francisco, CA | San Francisco, CA, United States |
| Employees | 5,000+ | 51–200 |
| Funding | Round at $60B valuation, including secondary sale | — |
| Best for | Data engineering, data science, analytics and AI teams at startups and global enterprises | Organizations that want search, vector retrieval, and observability on open source software without vendor lock-in. |
Pros and cons
Themes from the AI answers that mention each brand
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
OpenSearch
- Strong general database popularity
- Hybrid keyword-plus-semantic search with dense vectors
- Suited to broader search, logging, analytics, and observability
Data collected ·ChatGPT, Perplexity, Google AI Mode·coverage 100%·next run
Cite as: SlateIndex, “Databricks vs OpenSearch”, https://slateindex.ai/compare/databricks-vs-opensearch, data of Nov 2, 2026. Licence: CC BY 4.0.