vs

KDB.AI vs kdb+

KDB.AI: KX's vector database for time-aware AI search, with temporal similarity and hybrid retrieval. kdb+: Column-store time-series engine with the q language, a fixture of capital-markets tick data.

key differences

  • KDB.AI is primarily a vector database; kdb+ is time-series.
  • kdb+ is built for larger datasets (≤ 1 PB) than KDB.AI (≤ 10 TB).
  • Horizontal scaling is none in KDB.AI and manual in kdb+.
  • Transactions: KDB.AI offers none ACID; kdb+ offers limited.
  • Only KDB.AI has vector search.
  • Only kdb+ has joins, secondary indexes, json, stored procedures, pub/sub.

choose kdb-ai for

  • +Pattern matching in market and sensor time series
  • +RAG over financial documents with time constraints
  • +Anomaly and outlier detection

best at · Vector search, RAG, Time-series

choose kdb-plus for

  • +Equities, FX and futures tick capture
  • +Trade surveillance and best-execution analysis
  • +Quant research on historical market data
  • +Real-time risk and P&L

best at · Tick data, Time-series, Real-time analytics

overview
Primary model
Vector
Time-Series
Also supports
Time-Series
Columnar / OLAP, Relational
Type
Database engine
Database engine
Status
Active
Active
Developer
KX
KX
First release
2023
2003
Latest version
–
KDB-X 5.0.20261015 (Oct 15, 2026)
License
ProprietaryProprietary (free and commercial licences)
ProprietaryCommercial; KDB-X Community Edition free with resource limits
Free tier
✓
✓
popularity
WhichDB Score
4.9
31.8
Rank
#393
#75
GitHub stars
–
–
Stack Overflow questions
–
2.3K
scale & guarantees
Comfortable data size
Medium (≤ 10 TB)
Large (≤ 1 PB)
Horizontal scaling
None
Manual
Multi-region
None
None
ACID
None
Limited
Consistency
Strong
Strong
Schema
Strict
Strict
Architecture
Single node, Client server
In memory, Single node, Client server
deployment
Self-hosted
✓
✓
Vendor-managed cloud
—
✓
Serverless
—
—
Embedded
—
—
Edge
—
—
Clouds
AWS, Google Cloud, Azure
AWS
capabilities
Transactions
—
—
Joins
—
✓
Secondary indexes
—
✓
Full-text search
—
—
Vector search
✓
—
Geospatial
—
—
JSON
—
✓
Change data capture
—
—
Triggers
—
—
Stored procedures
—
✓
Materialized views
—
—
TTL / expiry
—
—
Pub/Sub
—
✓
Columnar storage
—
✓
In-memory
—
✓
Durable persistence
✓
✓
Compression
✓
✓
Encryption at rest
—
✓
Role-based access
—
—
Time travel
—
—
Branching
—
—
Online schema changes
—
—
Streaming ingest
—
✓
Offline sync
—
—
Runs in WebAssembly
—
—
interfaces
Query languages
KDB.AI Python API, REST API
q, qSQL, Python (PyKX)
Client languages
Python, q
Python, Java, C, C#
Best for
Vector search, RAG, Time-series, Tick data
Tick data, Time-series, Real-time analytics, Streaming

KDB.AI vs kdb+: FAQ

What is the difference between KDB.AI and kdb+?

KDB.AI: KX's vector database for time-aware AI search, with temporal similarity and hybrid retrieval. kdb+: Column-store time-series engine with the q language, a fixture of capital-markets tick data. KDB.AI is primarily a vector database; kdb+ is time-series. kdb+ is built for larger datasets (≤ 1 PB) than KDB.AI (≤ 10 TB). Horizontal scaling is none in KDB.AI and manual in kdb+.

When should I choose KDB.AI over kdb+?

Choose KDB.AI for pattern matching in market and sensor time series; RAG over financial documents with time constraints; and anomaly and outlier detection. Choose kdb+ for equities, FX and futures tick capture; trade surveillance and best-execution analysis; and quant research on historical market data.

Is KDB.AI or kdb+ more popular?

kdb+ ranks #75 on the WhichDB Score (31.8/100) and KDB.AI ranks #393 (4.9/100). Popularity is not fit: check the requirements that matter for your project.

Are KDB.AI and kdb+ open source?

No. KDB.AI is proprietary, closed-source software. No. kdb+ is proprietary, closed-source software. License: Commercial; KDB-X Community Edition free with resource limits.