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Real Time Analytics Database | CrateDB
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Your Real-Time Database
for Analytics, Search, and AI

From Ingest to Insights, Instantly.
Any Data, Any Scale, with SQL.

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"We needed a solution that could watch, record and analyze production in real time. CrateDB gives us the freedom to be cumulative and scale limitless - we found no alternative solution with such simplicity and efficiency.”
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"Working with CrateDB brings positive outcomes. The ingestion and throughput have very good performance, with 1 million values/sec, the horizontal scalability where we can add as many nodes as we need and the automatic query distribution across the whole cluster."
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"CrateDB allows us to do real-time dashboards on very big streaming and historic datasets in a simple way. We can scale the system easily as we grow the load and customers and have it all done with SQL."
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"Having a standardized SQL language is a big advantage with CrateDB. That makes it very easy for people to access this data and work with it in different tools like Grafana or Tableau."
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CrateDB is a lead in the time series database category on G2 winter 2026
G2 badge for Best Relationship for CrateDB Winter 2026 in the time series database category

CrateDB is a real time analytics database that ingests any data and makes it instantly queryable at scale. Execute complex aggregations, ad-hoc joins, hybrid search, and AI feature queries in seconds through a powerful distributed SQL engine.
CrateDB - Real Time Analytics Database

Real-Time Data Insights

Gain immediate access to real-time data and unlock the ability to make decisions in milliseconds. Whether it's responding to emerging trends, detecting anomalies, or optimizing workflows, CrateDB ensures data-driven actions happen at the speed of your business.

Turbocharged Aggregations

Run ad-hoc queries on billions of records in milliseconds, uncovering actionable insights at unprecedented speed. Powered by columnar storage, CrateDB delivers ultra-fast aggregations, enabling instant exploration of complex data relationships.

Hybrid Search Powered by Lucene 

Perform full-text, geospatial, vector similarity, and hybrid searches, seamlessly combining results from diverse data types and the most complex datasets, thanks to a fully distributed SQL query engine built on Apache Lucene.


Seamless AI Model Integration

Effortlessly integrate AI models to store, search, and query vectors, enabling real-time training, predictions, and decision-making. With this closed-loop system of continuous optimization, the database evolves alongside your business needs, enhancing AI-driven workflows.

 

Dynamic Schema and Indexing

Adapt seamlessly to evolving data types and schema changes without interrupting operations. Real-time data is immediately available for querying upon ingestion, even as your data structure shifts. The system dynamically optimizes indexing on the fly, ensuring fast, uninterrupted performance, regardless of fluctuating workloads or schema adjustments.

Built for Scale and Resilience

Manage massive data volumes, from millions to billions of records, while ensuring high-speed performance. Fault-tolerant, distributed architecture guarantees uninterrupted insights, scaling effortlessly to meet growing demands—even under heavy workloads or failures.

Real-Time Unified Data Layers

A New Era for Scalable Analytics, Search, and AI

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Successful companies using CrateDB

Enhanced Developer Productivity

Boost your developer productivity with native SQL for simple queries and quick onboarding. Analyze relational, JSON, time-series, geospatial, full-text, and vector data within a single system.

PostgreSQL compatibility ensures easy integration with third-party tools, enhancing compatibility and migration. Utilize the vector store to seamlessly integrate with AI/ML tools and LangChain, allowing you the freedom to choose your LLM and embedding algorithms.

The power and flexibility of the open-source licensing model liberates you from vendor lock-in, and provides support from the growing developer community.

 
        

/* Based on device data, this query returns the average
 * of the battery level for every hour for each device_id
 */
WITH avg_metrics AS (
    SELECT device_id,
       DATE_BIN('1 hour'::INTERVAL, time, 0) AS period,
       AVG(battery_level) AS avg_battery_level
    FROM devices.readings
    GROUP BY 1, 2 
    ORDER BY 1, 2
)
SELECT period,
       t.device_id,
       manufacturer,
       avg_battery_level  
FROM avg_metrics t, devices.info i
WHERE t.device_id = i.device_id 
      AND model = 'mustang'
LIMIT 10;


        
        
        

+---------------+------------+--------------+-------------------+
|    period     |  device_id | manufacturer | avg_battery_level |
+---------------+------------+--------------+-------------------+
| 1480802400000 | demo000001 |    iobeam    | 49.25757575757576 |
| 1480806000000 | demo000001 |    iobeam    | 47.375            |
| 1480802400000 | demo000007 |    iobeam    | 25.53030303030303 |
| 1480806000000 | demo000007 |    iobeam    | 58.5              |
| 1480802400000 | demo000010 |    iobeam    | 34.90909090909091 |
| 1480806000000 | demo000010 |    iobeam    | 32.4              |
| 1480802400000 | demo000016 |    iobeam    | 36.06060606060606 |
| 1480806000000 | demo000016 |    iobeam    | 35.45             |
| 1480802400000 | demo000025 |    iobeam    | 12                |
| 1480806000000 | demo000025 |    iobeam    | 16.475            |
+---------------+------------+--------------+-------------------+
Learn more about time-series data