A better database for
automation and alerting
Materialize is a database with stream processing internals: Use SQL to transform data in real-time, and event-driven primitives to automate it.
Ship real-time product notifications in hours, not weeks
Alerts and automated actions need to act fast - and on the right information. However, many applications are still built on a batch paradigm, fundamentally limiting how quickly notifications can be triggered.
With Materialize, software engineering teams can build real-time services with sub-second latencies, all while using the same SQL and scale they’ve used with traditional data warehouses. And with the strongest consistency guarantees, Materialize alleviates worries about false positives or incorrect triggers that have previously troubled product teams working with real-time data.
User-facing notifications
User-facing notifications
Customers expect only the most useful notifications to be delivered when they are most relevant. Build highly-specific notifications on high-volume, rapidly changing data - no need to wait for your data warehouse to run.
Fraud and anomaly detection
Fraud and bot management models need to work immediately to detect and eliminate anomalous activity faster than they can adapt and exploit. Detect fraud on large datasets at extremely low latencies - and easily adjust models as needed in SQL.
Risk Modeling
Instantly determine how much risk and volatility is present in a particular trade, investment, or series of cash flows. Use your existing SQL models to validate every trade in a portfolio in real-time, instead of in batches.
Monitoring and maintenance
Monitor and manage the health of networks, IoT devices, and connected fleets. Build dashboards for real-time visibility into conditions and locations, then automate alerts to status changes and better enable preventative maintenance.
Use an engine purpose built for real-time analytics
Materialize is built from the ground up to solve complex issues hindering adoption of streaming tools.
“Our data warehouse alerts run too slowly”
Data warehouses power many user-facing notifications and data models - but can only work in batches. Materialize incrementally maintains the results of SQL queries in real-time so alerts never run off of old data.
“Creating and updating notification logic is a hassle”
Hard-coded notification logic requires a ton of effort to update and maintain as business requirements shift. Materialize allows you to adjust and test using standard SQL, saving time both in the short and long term.
“We don’t have the data engineers for real-time alerts”
Anyone who knows standard SQL - including full-stack engineers, data scientists, or PMs - can build notification logic within Materialize, eliminating the need for long back-and-forth review cycles with data engineering.
“We can’t risk automation if our system gives bad data”
Don’t risk weird failure cases caused by eventual consistency. All results from Materialize reflect correct answers, meaning alerts and automated processes are never falsely triggered by late-arriving data.
“We use other systems for our notifications”
Materialize is postgres wire-compatible and acts like a standard postgres database. Keep your existing alerting and notification systems - but power them with real-time data.
“We need to run alerts at massive scale”
Materialize is designed for scale, and is powered by a stack of stream processors - Timely Dataflow and Differential Dataflow - that have been battle-tested by Fortune 100 companies in global deployments.
Featured Customer Story"With Materialize, we can write real-time SQL, the same way as we already are in Snowflake with batch while continuing to use dbt."
Read Customer story
Key Features
Incremental Materialized Views
The power of materialized views - but always up-to-date
Easily Connect Kafka
Easily manage streams from Kafka or Redpanda
Make Postgres Real-Time
Connect directly to any Postgres database via CDC.
dbt Integration
Use dbt to model data and create real-time analytics
Full SQL - including joins
Full support for joins, subqueries, CTEs, inserts, and deletes.
Presents as Postgres
Connect to the ecosystem of Postgres tools
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