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CrateDB

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Real-time analytics database for instant insights from any data, at any scale, with SQL.

Free plan available, paid tiers above
Freemium Data & Databases Analytics Real-Time Analytics
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Reviews on G2
85 reviews tracked

The Bottom Line

Price
Free plan available, paid tiers above. Compare plans

Key facts

  • Real-time analytics database for instant querying of diverse data at scale using SQL.
  • Supports complex aggregations, hybrid search (including vector similarity), and AI model integration.
  • Offers dynamic schema, high scalability, fault tolerance, and PostgreSQL compatibility for enhanced developer productivity.

Pros

  • Distributed SQL database
  • Time-series optimized
  • Good performance
  • Full-text search
  • Open source

Cons

  • Smaller community
  • Learning curve
  • Limited ecosystem
  • Documentation gaps
  • Less known

What is CrateDB?

Editorial review
CrateDB is a real-time analytics database designed to ingest and instantly query any data at scale. It enables users to execute complex aggregations, ad-hoc joins, hybrid search, and AI feature queries in seconds through its powerful distributed SQL engine. The platform is built for speed, offering turbocharged aggregations on billions of records in milliseconds, powered by columnar storage. It caters to businesses needing immediate access to real-time data for decision-making, anomaly detection, and workflow optimization. CrateDB supports various data types including relational, JSON, time-series, geospatial, full-text, and vector data within a single system. Its dynamic schema and indexing adapt to evolving data structures without interrupting operations, ensuring real-time data availability upon ingestion. With PostgreSQL compatibility, it integrates easily with third-party tools like Grafana and Tableau, and its vector store allows seamless integration with AI/ML tools and LangChain, offering flexibility in choosing LLMs and embedding algorithms. CrateDB is available as a fully managed service (DBaaS) or for deployment on preferred infrastructure, with an open-source licensing model to prevent vendor lock-in.

Available on: Web

how we evaluate Source cratedb.com ↗

Ratings Across the Web

4.4 (85 reviews)

CrateDB holds an aggregate rating of 4.4 out of 5 from 85 reviews across G2, last checked September 7, 2026.

G2 85 reviews
4.4/5

Ratings aggregated from independent review platforms. Learn more

Key Features

  • Distributed SQL database
  • Time series support
  • Full-text search
  • Geospatial queries
  • Machine learning
  • Horizontal scaling

Pricing Plans

Free Trial

Pricing checked Oct 5, 2026

CrateDB plans and prices, checked October 2026
PlanPriceDetails
Free

$0

Get started

  • 2 vCPUs
  • 2 GB RAM
  • 8 GB storage
+2 more
  • Shared environment
  • No credit card required
Shared

$0.073/per hour

Non-critical workloads

  • Up to 8 shared vCPUs
  • Up to 12 GB RAM
  • Up to 1 TB storage
+2 more
  • Daily backups
  • Dev support
Dedicated

$0.246/per hour

Production

  • Up to 144 vCPUs
  • Up to 495 GB RAM
  • Up to 72 TB storage
+3 more
  • Hourly backups
  • Uptime SLAs
  • Private Link
Custom

Custom

Large production

  • Unlimited nodes
  • Custom compute
  • Unlimited storage
+2 more
  • Premium support
  • Dedicated master nodes
Calculate your cost View full pricing

Is CrateDB worth the price?

Good value

CrateDB offers a generous Free tier and a very flexible Shared tier starting at $0.073 per hour, making it accessible for development and non-critical workloads.

The Dedicated tier, at $0.246 per hour, provides robust features for production. This pricing structure is fair and competitive, particularly for users needing scalable real-time analytics.

Hidden Costs & Gotchas

Overage charges for exceeding resource limits

Full CrateDB pricing: every plan, hidden costs and alternatives

Reviews

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4.4/5

Across 85 verified user reviews on G2

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Still deciding?

Most buyers shortlist 2 or 3 tools before committing. Pull a side-by-side comparison or browse the full alternatives shortlist below.

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CrateDB FAQ

How does CrateDB support real-time decision-making?

CrateDB is engineered for speed, allowing users to execute complex aggregations and ad-hoc joins on billions of records in milliseconds. This capability provides immediate access to real-time data, which is crucial for instant insights and timely decision-making.

Which teams would benefit most from using CrateDB?

Teams that require immediate access to real-time data for applications like anomaly detection, workflow optimization, and operational analytics would find CrateDB particularly beneficial. Its ability to handle diverse data types and perform turbocharged aggregations supports data-intensive operations.

How does CrateDB compare to ClickHouse for analytics workloads?

CrateDB offers a distributed SQL engine with PostgreSQL compatibility and supports a wider range of data types including relational, JSON, time-series, geospatial, full-text, and vector data within a single system. It also features dynamic schema and indexing, adapting to evolving data structures without interruption.

What kind of data types can CrateDB manage within a single system?

CrateDB supports a variety of data types, including relational, JSON, time-series, geospatial, full-text, and vector data. This allows for comprehensive data management and analysis without needing multiple specialized databases.

What are the main trade-offs when adopting CrateDB?

Adopting CrateDB may involve a learning curve due to its specialized nature, and it currently has a smaller community and a less extensive ecosystem compared to more established solutions. There may also be some documentation gaps that users need to navigate.

How is CrateDB priced?

CrateDB is available with a free tier, offering an entry point for users to explore its capabilities. Paid plans are also available, providing additional usage and features for more demanding requirements.

Can CrateDB integrate with artificial intelligence and machine learning tools?

Yes, CrateDB's vector store allows for seamless integration with AI/ML tools and platforms like LangChain. This provides flexibility in choosing different large language models (LLMs) and embedding algorithms for AI-driven applications.

Source: cratedb.com

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