kdb+
kdb+: A specialized, self-hosted engine for real-time and historical financial analytics. Ranked #4 of 36 in Time-Series Databases by our editors (8.9/10); pricing: Pricing on request; best for high-performance financial time-series processing.
At a glance
- Editor score8.9 / 10
- PricingPricing on request
- Best forHigh-performance financial time-series processing
- DeploymentBoth
- Facts checked22 Sep 2026
Where it wins
- Columnar storage with in-memory real-time processing
- Tickerplant, feedhandler, and partitioned historical database architecture
- Integrations across ODBC, Kafka, Java, Python, C, and R
Where it doesn't
- Self-hosted deployment requires infrastructure ownership
- Closed-source licensing limits source-level customization
- Pricing requires contacting sales
Our verdict on kdb+
kdb+ is a time-series database and analytics engine for organizations processing real-time and historical data. Its design combines columnar storage, in-memory execution, persistent databases, temporal data types, and the q programming and query language. KX documents applications across capital markets, defense, and high-tech manufacturing, including quantitative research, backtesting, execution analysis, risk management, surveillance, and streaming analytics. It is available for Linux, macOS, and Windows, with self-hosted deployment.
The architecture is particularly suited to financial workloads that combine live feeds with historical analysis. Feedhandlers and tickerplants support real-time ingestion, while historical databases can be partitioned by date. Segmented databases distribute data across storage devices, and temporal analytics support time-oriented queries. The real-time tickerplant and subscriber model gives teams a defined pattern for distributing incoming data, while q, qSQL, and SQL provide query options. These capabilities make kdb+ a focused choice for teams that need high-throughput time-series processing rather than a general-purpose database.
Platform fit is broad for a self-hosted system. ODBC enables external SQL queries, and integrations include Apache Kafka, Java, Python, C, and R. Pricing is contact-sales, so organizations evaluating deployment must engage KX for commercial terms and configuration. The main trade-off is operational ownership: teams manage a self-hosted, closed-source platform and work within its q-centered architecture. Financial institutions and engineering groups seeking specialized real-time and historical analytics should consider kdb+; teams that require open-source software or managed deployment should choose an alternative.
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kdb+ pricing
kdb+ fact sheet
| Free plan | Not verified |
|---|---|
| Paid from | Not verified |
| Deployment | Both |
| SQL support | Yes |
| Retention policies | Yes |
| Horizontal scaling | Yes |
| Query languages | q, q-SQL |
| Ingestion methods | tickerplant, feed handlers, batch mode, TCP/IP, Apache Kafka, Python, Java, C |
| Deployment | Cloud, Self-hosted |
| Platforms | Windows, macOS, Linux |
| Support | Community, Docs |
| Built for | Mid-market, Enterprise (editorial estimate) |
| Integrations | 17 integrations: Python, Java, C, C#, C++, Rust … See all → |
| Pricing | Pricing on request (source) |
| Website | kx.com |
| Facts checked | 22 Sep 2026 |
kdb+ integrations
kdb+ lists 17 integrations on its own site.
- Python
- Java
- C
- C#
- C++
- Rust
- R
- Apache Kafka
- MQTT
- JDBC
- Arrow
- Parquet
- Avro
- HDF5
- Protocol Buffers
- Solace
- Prometheus
Alternatives to kdb+
- Apache IoTDBA focused open-source choice for high-volume IoT ingestion, SQL, retention, and scaling.9.3
- Amazon TimestreamA managed AWS option with flexible ingestion, retention, SQL, and InfluxDB support.9.1
- LindormTSDBA broad compatibility layer for teams managing scalable telemetry and metrics workloads.9.0
kdb+ vs the competition
- kdb+ vs Apache IoTDB
- kdb+ vs Amazon Timestream
- kdb+ vs LindormTSDB
- kdb+ vs Prometheus
- kdb+ vs Grafana Mimir
- kdb+ vs InfluxDB
Compare kdb+ with any tool side by side →
Also Ranked In
kdb+ is ranked in 4 of our directories.
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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
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