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DatabricksUnified data, analytics and AI platform on an open lakehouse
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PineconeBuild knowledgeable AI
Comparison · Vector Databases · weekly run Nov 2

Databricks vs Pinecone

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

The short answer

Pinecone is the stronger AI pick in Vector Databases: it has a visibility score of 71.8 versus 1.4 for Databricks, and ranks ahead in 100% of the answers that name both.

Choose Databricks if…

  • You need ISO 27017 or ISO 27018 or ISO 27701 or SOC 1 or SOC 3 coverage
  • You prefer a larger, established vendor (5,000+ employees)
  • Lakehouse architecture combining data warehousing with data lake flexibility
  • Strong for machine learning, AI, and data engineering workloads

Choose Pinecone if…

  • You want the brand AI engines rank higher (71.8 vs 1.4)
  • AI answers describe it more positively (57% vs 35% positive)
  • You need HIPAA or GDPR coverage
  • Zero-ops, fully managed cloud service

AI visibility side by side

Latest weekly run · Nov 2

Metric Databricks Pinecone
Visibility score1.4%71.8%
Change vs last weekNewNew
Rank in Vector Databases#22#1
Share of voice0.8%14%
Mentions this run466
Positive in AI answers35%57%

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 2Databricks 1%

Databricks 0pp · Pinecone 0pp over 0 weekly runs.

Engine by engine

Pinecone leads on 3 of 3 engines

ChatGPT
1.9%
77%
AI Mode
1.3%
77.4%
Perplexity
1.1%
61.1%
DatabricksPinecone

Head to head in AI answers

5 engine answers name both brands

0Databricks ranked higher
5Pinecone ranked higher

Features, pricing & fit

DimensionDatabricksPinecone
Pricing model—Usage-based
Entry price—Free; paid from $20 / mo
Free plan—Yes
DeploymentAvailable across all major cloud providersFully managed cloud service, with an optional bring-your-own-cloud (BYOC) deployment
ComplianceISO 27001, ISO 27017, ISO 27018, ISO 27701, SOC 1, SOC 2 Type II, SOC 3SOC 2 Type II, HIPAA, GDPR, ISO 27001
SupportTechnical support on request, Technical documentationCommunity support via Discord on Starter, Free support with response SLAs available via Developer or Pro add-on, Pro support included on Enterprise and BYOC, Dedicated customer success and support SLAs on Enterprise
Founded20132019
HeadquartersSan Francisco, CANew York, NY
Employees5,000+51–200
FundingRound at $60B valuation, including secondary saleSeries B · $138M raised
Best forData engineering, data science, analytics and AI teams at startups and global enterprisesProduction AI applications, from solo developers and small teams to mission-critical enterprise deployments

Plans side by side

Databricks

Pricing not available.

Pinecone

Starter$0free
Builder$20month flat
Standard$50month minimum usage
Enterprise$500month minimum usage
Pinecone pricing

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

Pinecone

  • Zero-ops, fully managed cloud service
  • Easiest managed option to start with
  • Enterprise-grade reliability and scalability
  • Free tier and trial credits for testing
  • Most-used and widely adopted vector database
  • Monthly minimum charges on paid tiers
  • Free tier limits the number of vectors
  • Concern about vendor lock-in

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

Cite as: SlateIndex, “Databricks vs Pinecone”, https://slateindex.ai/compare/databricks-vs-pinecone, data of Nov 2, 2026. Licence: CC BY 4.0.