AI/ML Database
Open source AI/ML database, all with SQL
Hyper-fast. Queries in milliseconds.
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 text, _score
FROM word_embeddings
WHERE knn_match(embedding, (SELECT embedding FROM word_embeddings WHERE text ='Discovering galaxies'), 2)
ORDER BY _score DESC
|------------------------|--------|
| text | _score |
|------------------------|--------|
|Discovering galaxies |1 |
|Discovering moon |0.952381|
|Exploring the cosmos |0.840336|
|Sending the mission |0.250626|
|------------------------|--------|
Vector storage
With vector storage, you can easily store and retrieve embeddings generated by ML models, seamlessly integrating vectorized data with your existing datasets. It allows you to enrich your existing data with semantics, providing context that aligns with your data and enhancing explainability.

Advanced search capabilities
CrateDB offers advanced search capabilities through its similarity search and flexible filtering, combining full-text and vector search. Similarity search allows users to find similarities across any data represented as vectors, while the combination of full-text and vector search improves the search precision by enhancing semantic similarity and keyword matching. These features facilitate enhanced recommendations, anomaly detection, and other AI/ML use cases.

Ingestion

Native SQL support
CrateDB is an SQL database that implements the PostgreSQL Wire Protocol. With CrateDB, you can easily query even complex and dynamic schemas in a familiar SQL format, without the need to learn custom languages. The massive parallel execution of queries ensures fast response times, making it ideal for handling ad-hoc queries across large datasets, including those commonly encountered in AI/ML applications.

Ecosystem
CrateDB seamlessly integrates with your AI and analytics stack by leveraging the support of the PostgreSQL Wire Protocol. Take advantage of CrateDB's native SQL support for complex data analytics to accelerate the integration with AI models and optimize your AI projects.

Reduced TCO
CrateDB offers a low Total Cost of Ownership (TCO) by eliminating the need to manage multiple systems. It seamlessly integrates your data, keeping your (meta-)data and vector representations aligned without the complexity of data synchronization processes. With its use of native SQL, CrateDB simplifies development and ensures compatibility with existing systems.

CrateDB at AI & Big Data Expo
CrateDB's VP Product shares his vision for the future with multi-model SQL databases and Large Language Models.
Interested?
CrateDB is an open source distributed database designed for AI/ML use cases. It efficiently manages diverse data types and ensures real-time data accessibility for continuous model training and prediction. With vector storage and similarity search features, CrateDB unlocks new dimensions of efficiency in complex data analytics, pattern recognition, and AI. All of this is built on a scalable architecture that supports native SQL, facilitating streamlined querying and reducing system complexity. Whether in the cloud, on-premises, or at the Edge, CrateDB offers the flexibility and efficiency needed for all AI and ML operations.


