Materialize directly integrates with our third-party applications, BI tools, you name it. It’s really SQL.
Materialize helps you get access to the power of a stream processing engine, with the simplicity of a PostgreSQL-compatible developer interface.
CREATE SOURCE my_kafka_source FROM KAFKA BROKER 'kafka:9092' TOPIC 'my-topic' FORMAT BYTES;
CREATE MATERIALIZED VIEW my_view AS SELECT * FROM db.users u JOIN kafka.activities a ON u.id = a.user_id JOIN s3.logs l ON u.id = l.user_id;
-- Query like a traditional database SELECT * FROM my_view WHERE user_id=123; --Subscribe to receive changes in a query TAIL (SELECT * FROM my_view WHERE user_id=123);
Whereas other systems require ahead-of-time denormalization or round-trip processing for joins, Materialize offers low-latency support for multi-way joins and complex transformations. Write the same kind of complex SQL queries you would use on a traditional data warehouse - and get real-time results.
Materialize offers an easy SQL interaction layer to a stack of powerful stream processing engines - Timely Dataflow and Differential Dataflow. Already used in correctness-critical global production deployments by Fortune 100 companies, these battle-tested systems avoid many of the shortcomings of other approaches to stream processing.
Join hundreds of other Materialize users and connect directly with our engineers. Learn from our community, get help with your implementation, and let us know what you think! We’d love to hear from you.