The Data Warehouse for Operational Workloads.
Materialize is an Operational Data Warehouse: A cloud data warehouse with streaming internals, built for work that needs action on what’s happening right now.

The trusted operating platform of high-impact data teams.


Build data products that drive value through action.
Get operational data products into production faster with familiar SQL workflows on a real-time engine.
Real-Time & User-Facing Analytics
→Dashboards and data products need to be reactive to up-to-the-minute changes in your business.

Automation and Alerting
→Save time for your users, and build value by taking action or notifying at only the right moments.

Segmentation and Personalization
→Value of personalization, recommendations, dynamic pricing increases as latency of data aggregations approaches zero.

ML in Production
→Online feature stores need continually updated data, operators need to monitor and react to changes in ML effectiveness.

Traditional tools don't meet the requirements.
Cloud Warehouses are easy, but they get expensive when run continuously, and hit hard limits on latency and concurrency.
Stream Processors are fast, but they're a low-level tool, using them has a high-engineering cost, and results in complex architectures.
Materialize combines the best of both worlds.
Materialize is a fast, distributed data warehouse built on streaming internals.
Distributed and Cloud Native
Materialize separates storage and compute for a cloud-native architecture — and adds in a serving layer.
Results are always up-to-date
Work is done at the moment of data arrival, rather than query time, so that maintained results are available almost instantly.
Managed in standard SQL
Incrementally Maintained Views
Write complex SQL transformations as materialized views that efficiently update themselves as inputs change.
Learn MoreSliding Windows
Write queries that filter to a window of time anchored to the present, Materialize will update results as time advances.
Learn MoreSQL Alerting
Write alerts as SQL queries with filters and subscribe to new rows as they appear.
Learn MoreCREATE MATERIALIZED VIEW my_view AS
SELECT userid, COUNT(api.id), COUNT(pageviews.id)
FROM users
JOIN pageviews on users.id = pageviews.userid
JOIN api ON users.id = api.userId
GROUP BY userid;
userID | api_calls | pageviews |
---|---|---|
VPLaKV | 400 | 20 |
MN37Mt | 60 | 9 |
1fT4KY | 72 | 42 |
sT4QY | 10 | 342 |
Incrementally Maintained Views
Write complex SQL transformations as materialized views that efficiently update themselves as inputs change.
Learn MoreCREATE MATERIALIZED VIEW my_view AS
SELECT userid, COUNT(api.id), COUNT(pageviews.id)
FROM users
JOIN pageviews on users.id = pageviews.userid
JOIN api ON users.id = api.userId
GROUP BY userid;
userID | api_calls | pageviews |
---|---|---|
VPLaKV | 400 | 20 |
MN37Mt | 60 | 9 |
1fT4KY | 72 | 42 |
sT4QY | 10 | 342 |
Sliding Windows
Write queries that filter to a window of time anchored to the present, Materialize will update results as time advances.
Learn MoreCREATE MATERIALIZED VIEW my_window AS
SELECT date_trunc('minute', received_at),
COUNT(*) as order_ct, SUM(amount) as revenue
FROM orders
WHERE mz_now() < received_at + interval '5 minutes'
GROUP BY 1;
minute | order_ct | revenue |
---|
SQL Alerting
Write alerts as SQL queries with filters and subscribe to new rows as they appear.
Learn MoreSELECT userID, email, MAX(orders.id) as last_order
FROM users
JOIN orders ON orders.userID = users.id
GROUP BY userId, email
-- Use a filter to surface users with a high % of fraud
HAVING SUM(is_fraud) / COUNT(orders.id)::FLOAT > 0.5;
userID | last_order | |
---|---|---|
REOtIb | a@gmail.com | 13/12/2022 |
Y5KBE8 | b@yahoo.com | 9/12/2022 |
Wj7JQ0 | c@hotmail.com | 13/12/2022 |
tPCQ0 | d@xyz.com | 13/11/2022 |
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.
Active Replication
Use replication to increase availability, reduce downtime, scale seamlessly.
Low-Latency Serving Layer
Results can be maintained in memory, making read latency similar to Redis.
Secure and Compliant
SOC 2 Type 2 compliant, encrypted at rest, secure connectivity to your infra.
Empower your Team to Build Confidently With Live Data.

Streamline solutions to hard problems.
Materialize is built from the ground up to deliver where others have fallen short: incremental view maintenance that doesn't sacrifice consistency and correctness, and without limits on SQL complexity.

Keep the stack and workflows you love.
Get new capabilities without disruptive changes:

Replace bespoke architectures with SQL.
Save your stream processor for the most complex use cases, everything else can be SQL queries.

Make fresh data accessible across teams.
Run multiple workloads on the same data with ease:
- Shared Storage: access the same raw data, updated continually.
- Isolation of Compute: develop without resource contention.