# CrateDB

> Distributed SQL for analytics over mixed and high-cardinality data

CrateDB is an open-source distributed SQL database for real-time analytics and search, querying relational, JSON, time-series, geospatial, vector, and full-text data through one PostgreSQL-compatible interface.

Website: https://cratedb.com

## Use it when

- Sensor and industrial data arrives in mixed shapes: relational rows, nested JSON, time-series, geospatial, vectors, and full text behind one SQL surface.
- PostgreSQL wire compatibility matters; standard drivers and JDBC connect without an adapter.
- High-cardinality IoT data must stay queryable in near real time, and everything being indexed by default is worth its write cost.
- The alternative is a document store beside a time-series database beside a search index.

## Think twice when

- Raw scan throughput on flat tables is the benchmark; ClickHouse and Doris are built for exactly that.
- You rely on transactions or strict consistency; CrateDB is eventually consistent and has no transactions.
- Pre-aggregation is central to your serving model; there are no materialized views, so aggregates run at query time.

## How it runs

A shared-nothing cluster where every node ingests, stores, coordinates, and answers queries; tables shard with replicas across nodes, and scaling means adding nodes. Storage is Lucene-based with columnar and row structures per field. CrateDB Cloud is the managed option.

## Details

### General

| Attribute | Value |
| --- | --- |
| License | Open source (permissive) |
| SPDX identifier | Apache-2.0 |
| Deployment | Self-hosted, Managed, Hybrid |
| Workload | Interactive, Streaming |
| Operational complexity | Medium |
| Pricing | Free, Subscription |
| Language | Java |
| Repository | https://github.com/crate/crate |
| Documentation | https://cratedb.com/docs |
| Stars | 4.4k |

### OLAP Engines

| Attribute | Value |
| --- | --- |
| Specialization | Multi-model: relational, JSON, full-text, geospatial and vector |
| SQL dialect | PostgreSQL wire protocol |
| Joins | Hash and nested-loop joins, all join types |
| Updates and deletes | UPDATE and DELETE by query; no transactions, eventual consistency |
| Ingest to queryable | About a second: rows appear on table refresh, not on write |
| Storage format | Lucene-based columnar and row storage |
| Compute and storage | Shared-nothing cluster; every node ingests, stores and coordinates |
| Indexes | Indexed by default: inverted for text, BKD numeric and geo, HNSW vectors |
| Pre-aggregation | None: views run at query time; materialized views not supported |
| Concurrent users | Any node coordinates; shards answer in parallel across the cluster |

## Capabilities

- [OLAP Engines](https://matca.io/capabilities/olap-engine)

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Source: https://matca.io/cratedb
Last updated: 2026-08-31T11:40:48.628Z