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AI/ML Database

CrateDB is an open source, multi-model and distributed database that offers high performance, scalability and flexibility. It is designed to grow your Machine Learning and AI workloads. CrateDB enables a wide range of use cases across industries while reducing development time and total cost of ownership through a single, scalable platform with native SQL support.

Vector storage

With CrateDB's vector store, 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.



CrateDB can ingest, process and analyze multi-structured data and dynamic schemas – relational tables, complex objects and arrays, time-series, geospatial, and textual data. It can easily ingest millions of records per second, through data streaming or batches, and from various data sources, such as Amazon S3 and Kafka.

Native SQL support

CrateDB is a distributed database that implements native SQL and 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.



CrateDB seamlessly integrates with your AI/ML stack (LangChain, MLflow, PyCaret ...) and analytics stack (Tableau, PowerBI ...) by leveraging the support of the PostgreSQL Wire Protocol

View a sample list of integrations >


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.


White Paper: How to Build AI-driven Knowledge Assistants with a Vector Store, LLMs and RAG Pipelines

This white paper explores how CrateDB provides a scalable platform to build Generative AI applications that cover the requirements of modern applications, such as AI-driven knowledge assistants. CrateDB is not just handling vectors, but also provides in a single storage engine a unique combination of all the data types needed for end-to-end applications, including RAG pipelines.

How to Build AI-driven knowledge assistants

Demo – Harnessing CrateDB’s Multi-Model Capabilities for AI-Powered Applications

In this video, we explore the integration of CrateDB and PyCaret to detect anomalies in machine data, crucial for identifying potential failures or inefficiencies in technological systems. CrateDB's capability for handling large-scale data with ease pairs seamlessly with PyCaret's low-code approach to machine learning, offering a streamlined path to uncovering insights within vast datasets.

How to Build AI-driven Knowledge Assistants with a Vector Store, LLMs and RAG Pipelines

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. 


Webinar: Digital Twins & Gen AI on Azure

Explore how TGW, a global leader in logistics automation, digitally transformed warehouse operations using Azure. This session delves into the creation of automated warehouses and LLM-based internal Q&A system, answering general questions of employees, providing deep insights based on technical documentation and support tickets, and streamlining sales support. 

Additional AI/ML topics

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.

"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."
Marko Sommarberg Lead, Digital Strategy and Business Development ABB Learn more

Other resources on AI/ML databases