Crate provides a distributed SQL database that natively handles time‑series, JSON, relational, geospatial, full‑text, and vector data in a single engine. It automatically indexes all fields on ingestion, enabling sub‑second queries on billions of rows without pre‑aggregation, schema redesign, or separate search clusters, and scales horizontally on‑premises, in the cloud, or at the edge.
Funding
$14M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Organizations that need to analyze high‑velocity, heterogeneous data such as time‑series sensor streams, JSON documents, geospatial points, full‑text, or vector embeddings often must use multiple specialized databases, perform pre‑aggregation or ETL pipelines, and manage complex scaling and operational overhead. This limits real‑time insight and increases cost and latency.
Solution
CrateDB provides a single distributed SQL database that natively supports time‑series, JSON, relational, geospatial, full‑text, and vector data. It ingests millions of records per second, automatically indexes all fields, and makes fresh data queryable within milliseconds. Standard PostgreSQL‑compatible SQL (joins, CTEs, UDFs) lets users run ad‑hoc analytics, hybrid search, and AI‑ready queries without schema redesign or separate search clusters. The shared‑nothing architecture self‑balances, recovers from node failures, and scales horizontally on‑premises, in the cloud, or at the edge, eliminating DBA‑driven tuning and downtime.
Target Audience
Primary customers are data‑intensive enterprises such as IoT platform providers, energy utilities, manufacturing and smart‑city operators, as well as SaaS companies that require real‑time analytics, search, and AI features on large, evolving datasets.
Features
- Automatic indexing of every field on ingestion, enabling sub‑second queries on billions of rows
- Unified SQL engine that handles time‑series, JSON, relational, geospatial, full‑text, and vector workloads in a single query
- Distributed query execution with parallel processing across all nodes for high‑cardinality analytics
- Built‑in full‑text search (Lucene) and K‑nearest‑neighbor vector search accessible via SQL functions
- Real‑time ingestion pipelines (streaming connectors, batch imports) with millisecond latency to query
- Self‑managing shared‑nothing cluster: automatic sharding, replication, node failure recovery, and zero‑downtime scaling
- PostgreSQL wire protocol and standard drivers for seamless integration with BI tools, Grafana, Tableau, and custom applications
- Enterprise‑grade security (RBAC, encryption at rest/in‑transit, audit logging) and compliance certifications (ISO 27001, SOC 2)