The fastest way to build live data products you can trust.

CenterfieldVontiveCraneGeneral MillsPrizePicksFubo TVSuperscriptNanitVori

Why is it so hard to keep up with demands for
real-time views into your data?

OLTP Databases

OLTP Databases

Data Warehouse - OLAP

Data Warehouse - OLAP

Do-it-yourself (DIY)

Do-it-yourself (DIY)

Introducing Materialize

undefined

Create composable data products using complex transformations of live data without compromising trustworthiness.

Materialize is powered by a revolutionary engine

Streaming EngineResultsWriteRead

"Agents and LLMs are making queries directly and accessing data with complex transformations at incredible scale. We needed something that's actually doing the work upfront."

Sam Spelberg

Co-founder, CTO

Delphi

120x

reduction in page load times

60%

improvement in engineering productivity

Access via standard SQL

Incrementally Maintained Views

Write complex SQL transformations as materialized views that efficiently update themselves as inputs change.

Learn More

Built for JOINs

Chevron Down

Multi-way, complex join support, even across databases - all in standard SQL.

Learn More

Sliding Windows

Chevron Down

Write queries that filter to a window of time anchored to the present, Materialize will update results as time advances.

Learn More

SQL Subscriptions

Chevron Down

Write alerts as SQL queries with filters and subscribe to new rows as they appear.

Learn More
incremental.sql
CREATE 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 More
incremental.sql
CREATE 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

Built for JOINs

Multi-way, complex join support, even across databases - all in standard SQL.

Learn More
joins.sql
SELECT DISTINCT ON (auctions.id) 
   bids.amount, 
   auctions.item,
   auctions.seller
 FROM auctions, bids
 WHERE auctions.id = bids.auction_id
 ORDER BY auctions.id,
   bids.amount DESC,
   bids.buyer;
			
amount item seller

Sliding Windows

Write queries that filter to a window of time anchored to the present, Materialize will update results as time advances.

Learn More
sliding.sql
CREATE 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 Subscriptions

Write alerts as SQL queries with filters and subscribe to new rows as they appear.

Learn More
alerting.sql
SUBSCRIBE (
  SELECT userID, email, MAX(orders.id) AS last_order
  FROM users
  JOIN orders ON orders.userID = users.id
  GROUP BY userId, email
  HAVING SUM(is_fraud) / COUNT(orders.id)::FLOAT > 0.5
);
userID email last_order
REOtIb 13/12/2025
Y5KBE8 9/12/2025
Wj7JQ0 13/12/2025
tPCQ0 13/11/2025
Checkmark
Checkmark
Checkmark
Checkmark

For use cases that get better with
fresher data
and more data sources.

 

Data-intensive UIs

 

Generative AI

 

Real-Time Process Optimization

Learn More  →
 

Automation and Alerting

Learn More  →
 

Online Feature Store

Learn More  →
 

Anomaly Detection

Three patterns for simplifying your data architecture

Query Offload

Query Offload

Integration Hub

Integration Hub

Operational Data Mesh

Operational Data Mesh

Seamlessly integrate with your existing stack

Loan eligibility rule calculation time decreased by 98.15%, dropping from 27 seconds to half a second.

Wolf Randall
Wolf Randall Director, Data Products, Vontive

Get Started with Materialize