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In Materialize, indexed views and materialized views maintain up-to-date query results. This allows Materialize to serve fresh query results with low latency.

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Overview

Materialize provides multiple ways to serve and consume your data:
  • Query results - Use SELECT statements to query point-in-time results with PostgreSQL-compatible clients
  • Stream updates - Use SUBSCRIBE to receive continuous streams of changes as they occur
  • External sinks - Write data to external systems like Kafka, S3, or Snowflake
  • BI tools - Connect business intelligence and data visualization tools

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Query Results

Materialize is wire-compatible with PostgreSQL, which means you can use standard PostgreSQL clients to query data: 
SELECT region.id, sum(purchase.total)
FROM mysql_simple_purchase AS purchase
JOIN mysql_simple_user AS user ON purchase.user_id = user.id
JOIN mysql_simple_region AS region ON user.region_id = region.id
GROUP BY region.id;
Key benefits:
  • Queries against indexed and materialized views return results instantly from memory
  • Low-latency responses ideal for operational applications
  • Compatible with any PostgreSQL client library
Learn more in Query Results.

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Stream Updates

For applications that need real-time updates, use SUBSCRIBE to stream changes: 
BEGIN;
DECLARE c CURSOR FOR SUBSCRIBE my_view;
FETCH ALL c WITH (timeout='1s');
Key benefits:
  • Receive incremental updates as data changes
  • Power event-driven architectures
  • Replicate the complete history of a relation
Learn more in Subscribe.

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Sinks

Sinks write Materialize data to external systems for downstream consumption: Supported destinations:
  • Kafka and Redpanda
  • Amazon S3
  • Snowflake
  • Iceberg
  • Third-party integrations (Census, etc.)
CREATE SINK kafka_sink
  FROM my_materialized_view
  INTO KAFKA CONNECTION kafka_connection (TOPIC 'results')
  KEY (id)
  FORMAT JSON
  ENVELOPE UPSERT;
Key benefits:
  • Automatically propagate changes to external systems
  • Exactly-once delivery guarantees (Kafka)
  • Multiple format options (Avro, JSON, Parquet)
Learn more in Kafka Sinks.

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Performance Considerations

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Indexed and Materialized Views

Performing a SELECT on an indexed view or materialized view is Materialize’s ideal operation. When receiving such queries, Materialize quickly returns the maintained results from memory.

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Ad-hoc Queries

Queries that can’t simply read from an index will create an ephemeral dataflow to compute the results. These dataflows are bound to the active cluster and are removed as soon as results are returned.

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Cluster Management

You can control which cluster executes queries: 
SET cluster = my_cluster;
Best practice: Avoid putting sinks on the same cluster that hosts sources to allow for blue/green deployments.

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Client Libraries

Materialize works with PostgreSQL client libraries across languages:

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BI Tools

Connect popular business intelligence and data visualization tools:
  • Tableau
  • Power BI
  • Metabase
  • Looker
  • Hex
  • Deepnote
  • Excel

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Next Steps

Query Results

Query Materialize using SELECT statements

Subscribe

Stream real-time updates with SUBSCRIBE

Kafka Sinks

Write data to Kafka topics

BI Tools

Connect visualization tools

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