Strong Consistency Guarantees for Streaming Data
Materialize guarantees strict serializable consistency that is standard in databases, but unprecendented in distributed stream processors.
The Streaming Database You Already Know How to Use
Materialize is a fast, distributed SQL database built on streaming internals.
Trusted by data and engineering teams
View Customer Stories.
Consistency, Scalability, Low Latency: Pick Three
The stream processor at the heart of Materialize proactively computes results with strong consistency and sub-second latency — all in a distributed, cloud-native architecture that allows for unbounded scale.
SQL Control Plane
Key Features
Presents as PostgreSQL
Manage and query Materialize using any Postgres driver or tool.
Built for JOINs
Multi-way, complex join support across real-time streams - all in standard SQL.
Separate Storage & Compute
Data is stored cheaply, compute scales independently and without limits.
Incremental Compute Engine
Instead of re-computing on every query, results are updated as data changes.
Active Replication
Use replication to increase availability, reduce downtime, scale seamlessly.
Low-Latency Reads
Results can be maintained in memory, making read latency similar to Redis.
What Can You Build with Materialize?
Data Engineers and Developers use Materialize as a better engine for cutting-edge data products.
Real-Time Analytics
Use the same ANSI SQL from data warehouses to build real-time views that serve internal and customer-facing dashboards, APIs and apps.
Automation and Alerting
Build user-facing notifications, fraud and risk models, and automated services using event-driven SQL primitives in a streaming database.
Segmentation and Personalization
Build engaging experiences with customer data aggregations that are always up-to-date: personalization, recommendations, dynamic pricing and more.
ML Ops
Power online feature stores with continually updated data, monitor and react to changes in ML effectiveness - all in standard SQL.
Why Materialize?
Built from the ground up to solve the hard problems in data.
Consistency in Streaming →
Multi-way and Cross-Stream Joins
Write the same kinds of complex, multi-way SQL joins you would use on a traditional data warehouse. Materialize maintains the joins efficiently in memory and serves real-time results.
PostgreSQL Up Front, Timely Dataflow Underneath
Materialize expands access to powerful stream processing capabilities of Timely and Differential Dataflow by wrapping them in a familiar and accessible SQL layer that is wire-compatible with Postgres.
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Works with Your Existing Data Stack
PostgreSQL
Streaming infrastructure is not required to use Materialize for real-time computation. Connect directly to any Postgres database via CDC and continually ingest data as it changes.
dbt
Run your existing dbt models on top of streaming data in Materialize, and dbt persists a materialized view. No matter how much or how frequently your data arrives, your model will stay up to date.
Kafka
Connect multiple Kafka topics to Materialize and easily explore, transform, and join streaming datasets - and sink maintained SQL query results downstream to new, enriched Kafka topics.
Trusted By Data Teams
Think Declaratively, Act Incrementally
Materialize helps you get access to the power of a stream processing engine, with the simplicity of a PostgreSQL-compatible developer interface.
Fast
Millisecond-level latency through incrementally-updated views.
Familiar
Control it with ANSI-standard SQL. Connect with Postgres drivers.
Fully-Featured
Support for multi-way joins, subqueries, upserts, deletes, CTEs.
Sign Up for Early Access
Register for early access to start building real-time analytics dashboards and live applications.
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