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DatabricksUnified data, analytics and AI platform on an open lakehouse
vs
QdrantOpen-Source Vector Search Engine written in Rust
Comparison · Vector Databases · weekly run Nov 2

Databricks vs Qdrant

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

The short answer

Qdrant is the stronger AI pick in Vector Databases: it has a visibility score of 60.5 versus 1.4 for Databricks, and ranks ahead in 100% of the answers that name both.

Choose Databricks if…

  • 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
  • Strong for machine learning, AI, and data engineering workloads

Choose Qdrant if…

  • You want the brand AI engines rank higher (60.5 vs 1.4)
  • AI answers describe it more positively (68% vs 35% positive)
  • You need a self-hosted or on-premises option
  • You need SOC 2 Type 2 or HIPAA coverage

AI visibility side by side

Latest weekly run · Nov 2

Metric Databricks Qdrant
Visibility score1.4%60.5%
Change vs last weekNewNew
Rank in Vector Databases#22#2
Share of voice0.8%13.4%
Mentions this run463
Positive in AI answers35%68%

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 · Qdrant 0pp over 0 weekly runs.

Engine by engine

Qdrant leads on 3 of 3 engines

ChatGPT
1.9%
71.8%
AI Mode
1.3%
59.4%
Perplexity
1.1%
50.2%
DatabricksQdrant

Head to head in AI answers

5 engine answers name both brands

0Databricks ranked higher
5Qdrant ranked higher

Features, pricing & fit

DimensionDatabricksQdrant
Pricing model—Usage-based
Entry price—Contact sales
Free plan—Yes
DeploymentAvailable across all major cloud providersManaged cloud, hybrid cloud, private cloud (air-gapped), self-hosted on-premises, and edge
ComplianceISO 27001, ISO 27017, ISO 27018, ISO 27701, SOC 1, SOC 2 Type II, SOC 3SOC 2 Type 2, HIPAA
SupportTechnical support on request, Technical documentationCommunity support via Discord on the free tier, Standard tier: email and ticket portal, 10x5 business hours, Premium tier: 24/7 support with private Slack, Discord or Teams channels, Enterprise tier: custom response SLA and advisory services
Founded20132021
HeadquartersSan Francisco, CABerlin, Germany
Employees5,000+51–200
FundingRound at $60B valuation, including secondary saleSeries B · $88M raised
Best forData engineering, data science, analytics and AI teams at startups and global enterprisesDevelopers and teams building RAG, semantic search and recommendation systems that need hybrid search and metadata filtering, either self-hosted or managed

Plans side by side

Databricks

Pricing not available.

Qdrant

Free Tier$0forever
Standard TierCustomusage-based
Premium TierCustomminimum spend required
Qdrant 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

Qdrant

  • High performance and memory efficiency, written in Rust
  • Strong metadata and complex payload filtering
  • Free tier for prototyping and testing
  • Open-source option with flexible self-hosting
  • Strong default choice for startups and production RAG

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

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