Vector Databases · crate

crate

CrateDB is a distributed SQL database designed for real-time analytics and time-series data at scale. It combines PostgreSQL compatibility with Lucene-based search, horizontal scalability, and containerization support, making it suitable for IoT, analytics, and massive data ingestion workloads.

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Source: GitHub — github.com/crate/crate

4.4k

GitHub stars

603

Forks

Java

Primary language

Apache-2.0

License (OSI-approved)

Key facts

Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.

Field	Value
Repository	crate/crate
Owner	crate
Primary language	Java
License	Apache-2.0 — OSI-approved
Stars	4.4k
Forks	603
Open issues	306
Latest release	6.3.4 (2026-06-22)
Last updated	2026-07-07
Source	https://github.com/crate/crate

What crate is

Java-based distributed SQL engine providing PostgreSQL wire protocol and HTTP API interfaces, with built-in full-text search (Lucene), geospatial support, time-series optimizations, and auto-sharding/replication. Operates as a shared-nothing, horizontally scalable cluster with parallel query execution across nodes.

Quickstart

Get the crate source

Clone the repository and explore it locally.

terminalbash

1git clone https://github.com/crate/crate.git2cd crate3# follow the project's README for install & configuration

Need it deployed, integrated, or customized instead? DEV.co ships production installs.

Best use cases

Industrial IoT & Sensor Analytics

Ingest tens of thousands of records/second from distributed sensors and devices; query time-series data with SQL for anomaly detection, trend analysis, and real-time dashboards without ETL pipelines.

Real-Time Log & Event Analytics

Centralize and query logs, application events, and operational metrics at massive scale; perform ad-hoc SQL queries on structured and semi-structured event streams for observability and compliance.

Geospatial & Location-Based Analytics

Store and analyze geographic data (geo-coordinates, polygons) with native geospatial types; support real-time proximity queries, fleet tracking, and location intelligence at scale.

Implementation considerations

Cluster sizing and sharding strategy must be planned upfront; auto-sharding simplifies initial deployment but resizing and rebalancing are operationally involved.
PostgreSQL wire protocol compatibility reduces client code changes, but CrateDB-specific features (full-text search, geospatial) may require custom SQL.
Heap size tuning (e.g., CRATE_HEAP_SIZE) and JVM memory management are critical for performance; requires Java operational expertise.
Data modeling for time-series (partitioning strategy, retention policies) should be designed early to avoid expensive migrations.
Docker and Kubernetes integration is well-documented, but multi-region and hybrid cloud deployments require planning around cluster consensus and network latency.

When to avoid it — and what to weigh

ACID Transaction Requirements — CrateDB is optimized for analytical workloads; traditional multi-row ACID transactions and strong consistency guarantees are not the primary design focus.
Small Data / Low Throughput — Distributed overhead and operational complexity favor workloads with high data volume or ingest rates; single-node relational databases (PostgreSQL, MySQL) are simpler for modest data.
Minimal Operational Overhead — Distributed clusters require monitoring, rebalancing, sharding strategy, and cluster management; simpler managed DBaaS offerings may be preferable if operational complexity is unacceptable.
Proprietary Vendor Lock-In Concerns — Although Apache-2.0 licensed, CrateDB is primarily maintained by Crate.io; migration path and long-term community support are dependent on vendor viability.

License & commercial use

Apache License 2.0 (Apache-2.0): permissive open-source license allowing free use, modification, and distribution with minimal restrictions. Requires copyright notice and license inclusion in distributions.

Apache-2.0 permits commercial use without explicit per-seat licensing. However, Crate.io also offers CrateDB Cloud (managed DBaaS) with proprietary terms. For large-scale production deployments, review Crate.io's commercial support offerings and SLAs separately; self-hosted Apache-2.0 use is unrestricted.

DEV.co evaluation signals

Editorial assessment — not user reviews. Directional, with an explicit confidence level.

Signal	Assessment
Maintenance	Active
Documentation	Strong
License clarity	Clear
Deployment complexity	Moderate
DEV.co fit	Good
Assessment confidence	High

Security considerations

README references a security reporting policy (SECURITY.md) and responsible disclosure, indicating security awareness. Apache-2.0 source code is publicly available for code review. No claims are made about encryption, authentication, or access control in the provided data—verify threat model, TLS support, user management, and audit logging separately. For sensitive workloads, evaluate cluster hardening, network isolation, and compliance (HIPAA, GDPR, etc.) requirements against current features.

Alternatives to consider

PostgreSQL + TimescaleDB

Strong if you prefer a single mature PostgreSQL instance with time-series extensions; simpler operational model, but less horizontal scalability for massive IoT ingestion.

ClickHouse

Purpose-built OLAP columnar database with superior compression and query speed for analytics; lacks PostgreSQL compatibility and geospatial support but excels at pure analytical workloads.

Elasticsearch

Distributed search and analytics engine with full-text and time-series capabilities; more mature in distributed search, but SQL support is secondary and requires additional tooling (Kibana, Logstash) for analytics.

Software development agency

Build on crate with DEV.co software developers

Evaluate CrateDB's fit for your IoT, time-series, or real-time analytics use case. Review cluster architecture, operational requirements, and integration strategy with your team. Consider a proof-of-concept with Docker or Kubernetes before committing to production.

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crate FAQ

Is CrateDB a replacement for PostgreSQL?

No. CrateDB is optimized for distributed analytics and high-throughput ingestion; it offers PostgreSQL wire protocol compatibility but is not a drop-in replacement. Use PostgreSQL for traditional OLTP workloads and CrateDB for OLAP/time-series at scale.

Can I run CrateDB in production without Crate.io support?

Yes. Apache-2.0 license permits self-hosted production use. However, CrateDB is a complex distributed system; operational support, training, and professional services from Crate.io are available if needed.

What is the minimum cluster size?

Single-node deployments are supported (e.g., Docker with `-Cdiscovery.type=single-node`). Production deployments typically require at least 3 nodes for fault tolerance and high availability.

Does CrateDB support transactions?

CrateDB supports statement-level consistency and eventual consistency in distributed clusters. Full ACID multi-row transactions are not available; it is optimized for read-heavy analytics and append-heavy time-series workloads.

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