Your Unified Data Layer
for Analytics, Search, and AI
From Ingest to Insights in Real Time
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 of records to petabytes, 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
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 |
+---------------+------------+--------------+-------------------+
/* Return the name and truncated description for the 5 Chicago community
areas with populations over 50,000 people. */
SELECT name,
details['population'] AS population,
concat(left(details['description'], 25), '...') AS description
FROM community_areas
WHERE details['population'] > 50000
ORDER BY details['population'] DESC
LIMIT 5;
+-----------------+------------+------------------------------+
| name | population | description |
+-----------------+------------+------------------------------+
| NEAR NORTH SIDE | 105481 | The Near North Side is th... |
| LAKE VIEW | 103050 | Lakeview, also spelled La... |
| AUSTIN | 96557 | Austin is one of 77 commu... |
| WEST TOWN | 87781 | West Town, northwest of t... |
| BELMONT CRAGIN | 78116 | Belmont Cragin is one of ... |
+-----------------+------------+------------------------------+
SELECT text, _score
FROM word_embeddings
WHERE knn_match(embedding,[0.3, 0.6, 0.0, 0.9], 2)
ORDER BY _score DESC;
|------------------------|--------|
| text | _score |
|------------------------|--------|
|Discovering galaxies |0.917431|
|Discovering moon |0.909090|
|Exploring the cosmos |0.909090|
|Sending the mission |0.270270|
|------------------------|--------|
SELECT show_id, title, director, country, release_year, rating, _score
FROM "netflix_catalog"
WHERE MATCH(title_director_description_ft, 'title^2 Friday') USING best_fields
AND type='Movie'
ORDER BY _score DESC;
+---------+------------------------------------+-------------------+----------------------+--------------+--------+-----------+
| show_id | title | director | country | release_year | rating | _score |
+---------+------------------------------------+-------------------+----------------------+--------------+--------+-----------+
| s1674 | Black Friday | Anurag Kashyap | India | 2004 | TV-MA | 5.6455536 |
| s6805 | Friday the 13th | Marcus Nispel | United States | 2009 | R | 3.226806 |
| s1038 | Tuesdays & Fridays | Taranveer Singh | India | 2021 | TV-14 | 3.1089375 |
| s7494 | Monster High: Friday Night Frights | Dustin McKenzie | United States | 2013 | TV-Y7 | 3.0620003 |
| s3226 | Little Singham: Mahabali | Prakash Satam | NULL | 2019 | TV-Y7 | 3.002901 |
| s8233 | The Bye Bye Man | Stacy Title | United States, China | 2017 | PG-13 | 2.9638999 |
| s8225 | The Brawler | Ken Kushner | United States | 2019 | TV-MA | 2.8108454 |
+---------+------------------------------------+-------------------+----------------------+--------------+--------+-----------+
/* Using 311 data from the City of Chicago, this query returns 5 open
work orders for locations closest to the Willis Tower. */
SELECT srnumber,
srtype,
locationdetails['streetaddress'] AS address,
distance(
'POINT(-87.636256 41.8786492)'::GEO_POINT,
locationdetails['location']
) / 1000 AS distance_km
FROM three_eleven_calls
WHERE status != 'Completed'
ORDER BY distance_km ASC
LIMIT 5;
+---------------+-----------------------------------------------+--------------------+---------------------+
| srnumber | srtype | address | distance_km |
+---------------+-----------------------------------------------+--------------------+---------------------+
| SR24-00711535 | Cab Feedback | 200 S WACKER DR | 0.09800707616741176 |
| SR24-00694851 | No Building Permit and Construction Violation | 300 W ADAMS ST | 0.1346164665090538 |
| SR24-00651822 | Sign Repair Request - All Other Signs | 111 SW WACKER DR | 0.20355339153863516 |
| SR24-00608464 | Building Violation | 235 W VAN BUREN ST | 0.26374860571526554 |
| SR24-00608655 | Building Violation | 235 W VAN BUREN ST | 0.26374860571526554 |
+---------------+-----------------------------------------------+--------------------+---------------------+
Streamlined Operations
Experience a cost-efficient, robust, and scalable architecture that delivers high performance at any scale. Eliminate the hassle of combining and synchronizing different databases, reducing overhead, and minimizing your carbon footprint.
Ensure high availability with automatic failover, recovery, and replication, keeping your data safe and accessible. The resilient architecture detects failures and maintains cluster health, offering peace of mind even in distributed environments.
Choose from multiple deployment models: DBaaS, hybrid cloud, of self-managed, providing flexibility to meet your operational needs, even for Edge deployment with limited connectivity. Whether you're running on a single laptop or dozens of servers with terabytes of data, seamlessly scale from prototype to production.
Introduction to CrateDB
Turbocharge your aggregations, search and AI models and get real-time insights
Upcoming Events
Register now for our joint webinar with our Partner Axcess.io "From Data to Decisions: How GenAI Supports Time-Series Monitoring and Manual...
Join us at the Hannover Messe 2025 happening on March 31- April 4.