SaaS
CrateDB helps SaaS companies turn massive volumes of data into actionable insights. It ingests and analyzes user behavior, metrics, and logs in real time. With distributed SQL and scalable architecture, CrateDB delivers speed, flexibility, and cost efficiency.
Real-time insights for your customers
Deliver analytics dashboards, user metrics, and event streams in real time. CrateDB handles high-ingest workloads and complex queries simultaneously, ensuring fast responses even as your data grows.

Effortless scalability
Add or remove nodes to handle fluctuating workloads and user growth. CrateDB’s shared-nothing architecture ensures seamless horizontal scaling with no downtime.

Cost-efficient operations
Use hot, warm, and cold data tiers to manage costs while maintaining performance for recent and historical data. Deploy on any cloud, on-premises, or hybrid environment for maximum flexibility.

Multi-model simplicity

AI-powered features
Store and query embeddings, perform vector similarity search, and combine them with your application data. Easily integrate AI-driven recommendations, semantic search, and personalization into your SaaS product.

Built-in reliability
CrateDB ensures high availability and fault tolerance by automatically replicating and rebalancing data. Keep your platform responsive and resilient, even during maintenance or node failures.


"It is through the use of CrateDB that we are able to offer our large-scale video analytics component in the first place. Comparable products are either not capable of handling the large flood of data or they are simply too expensive."
Daniel Hölbling-Inzko
Senior Director of Engineering - Analytics
Bitmovin


Shoott is a photography company that offers affordable, professional photoshoots through a seamless booking process and personalized customer experience. They faced a critical challenge when their analytics engine, powered by Rockset, was discontinued.
"CrateDB has enabled us to maintain seamless analytics despite the transition from Rockset. With its flexible schema and powerful indexing, we’ve been able to handle complex data efficiently and reduce manual overhead. This has allowed our teams to focus on delivering key insights while ensuring our systems remain scalable for future growth."
Dmitry Feoktistov
Development Team Lead
Shoott




"I started looking at CrateDB and was impressed by the quality of the code. Switching from MySQL to CrateDB took a couple of days. It was very convenient to integrate CrateDB into our existing base even though it was written for a different database. The fact that CrateDB uses SQL lowers the barrier to entry when using distributed search. And on top of that, with CrateDB you can replace MongoDB and Elastisearch with one scalable package."
Jeff Nappi
Director of Engineering
ClearVoice


"Postgres couldn't keep up with the data we have; Datastax Enterprise had ingest scaling issues with spatial data; Cassandra didn't have spatial query operations. CrateDB was the only database we found that could smoothly process data for our users and for our data science team. We fell in love with it immediately."
Kartik Venkatesh
CTO
Spatially Health


"Most of the cars in our customers' fleets are in use almost 24 hours a day, and we need to store and analyse the massive amounts of data they generate in real time. We tried a few different SQL and NoSQL databases, and CrateDB offered the best combination of high performance, scalability and ease of use."
Mark Sutheran
Founder
Clickdrive.io


"CrateDB was a better solution for our needs than any other SQL or NoSQL database we tried. It was easy to migrate code off of our legacy SQL database and onto CrateDB to immediately benefit from its data flexibility and scalable performance."
Sheriff Mohamed
Director of Architecture
GolfNow








"We explored several solutions like Clickhouse, Rockset, Snowflake, among others. CrateDB is a great fit for us. Having a Cloud offer was perfect along with having the nested structure we were looking for."
David Sargeant
Director of Software Engineering
GovSpend
