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https://github.com/MaterializeInc/materialize

The Cloud Operational Data Store: use SQL to transform, deliver, and act on fast-changing data.
https://github.com/MaterializeInc/materialize

data-warehouse database distributed-systems kafka materialized-view operational-data-warehouse postgresql postgresql-dialect rust sql stream-processing streaming streaming-data

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The Cloud Operational Data Store: use SQL to transform, deliver, and act on fast-changing data.

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[](https://materialize.com)



Materialize is the **cloud operational data store** purpose-built to use SQL to

transform, deliver, and act on fast-changing data.



Using SQL and common tools in the wider data ecosystem, Materialize allows you

to build real-time automation, engaging customer experiences, and interactive

data products that drive value for your business while reducing the cost of

[data freshness](https://materialize.com/blog/decouple-cost-and-freshness/).



## Get started



Ready to try out Materialize? [Sign up](https://materialize.com/register/) to get started! 🚀



Have questions? We'd love to hear from you:

  * [Join our Slack](https://materialize.com/s/chat)

  * [Send us mail](https://materialize.com/contact/)



## About



Materialize is designed to help you interactively explore your streaming data, perform analytics against live relational data, or increase data freshness while reducing the load of your dashboard and monitoring tasks. The moment you need a refreshed answer, you can get it in milliseconds.



It focuses on providing correct and [consistent](https://materialize.com/docs/overview/isolation-level/) answers with minimal latency, and does not ask you to accept either approximate answers or eventual consistency. Whenever Materialize answers a query, that answer is the correct result on some specific (and recent) version of your data. Materialize does all of this by recasting your SQL queries as *dataflows*, which can react efficiently to changes in your data as they happen.



Our fully managed service is cloud native, featuring **high availability**, via

multi-active replication, **horizontal scalability**, by seamlessly scaling

dataflows across multiple machines, and **near infinite storage**, by

leveraging cloud object storage (e.g., Amazon S3).



We support a large fraction of PostgreSQL features, and are actively working on supporting more built-in PostgreSQL functions. Please file an issue if something doesn't work as expected!



## Get data in



Materialize can read data from [Kafka](https://materialize.com/docs/sql/create-source/kafka/) (and other Kafka API-compatible systems like [Redpanda](https://materialize.com/docs/integrations/redpanda/)), directly from a [PostgreSQL](https://materialize.com/docs/sql/create-source/postgres/) or [MySQL](https://materialize.com/docs/sql/create-source/mysql/) replication stream, or from SaaS applications [via webhooks](https://materialize.com/docs/sql/create-source/webhook/). It also supports regular database tables to which you can insert, update, and delete rows.



## Transform, manipulate, and read your data



Once you've got the data in, define views and perform reads via the PostgreSQL protocol. Use your favorite SQL client, including the `psql` you probably already have on your system.



Materialize supports a comprehensive variety of SQL features, all using the PostgreSQL dialect and protocol:



-   Joins, joins, joins! Materialize supports multi-column join conditions, multi-way joins, self-joins, cross-joins, inner joins, outer joins, etc.

-   Delta-joins avoid intermediate state blowup compared to systems that can only plan nested binary joins - tested on joins of up to 64 relations.

-   Support for subqueries. Materialize's SQL optimizer performs subquery decorrelation out-of-the-box, avoiding the need to manually rewrite subqueries into joins.

-   Materialize can incrementally maintain views in the presence of arbitrary inserts, updates, and deletes. No asterisks.

-   All the aggregations: `min`, `max`, `count`, `sum`, `stddev`, etc.

-   `HAVING`

-   `ORDER BY`

-   `LIMIT`

-   `DISTINCT`

-   JSON support in the PostgreSQL dialect including operators and functions like `->`, `->>`, `@>`, `?`, `jsonb_array_element`, `jsonb_each`. Materialize automatically plans lateral joins for efficient `jsonb_each` support.

-   Nest views on views on views!

-   Multiple views that have overlapping subplans can share underlying indices for space and compute efficiency, so just declaratively define _what you want_, and we'll worry about how to efficiently maintain them.



### Just show us what it can do!



Here's an example join query that works fine in Materialize, `TPC-H` query 15:



```sql

CREATE SOURCE tpch

  FROM LOAD GENERATOR TPCH (SCALE FACTOR 1)

  FOR ALL TABLES;



-- Views define commonly reused subqueries.

CREATE VIEW revenue (supplier_no, total_revenue) AS

    SELECT

        l_suppkey,

        SUM(l_extendedprice * (1 - l_discount))

    FROM

        lineitem

    WHERE

        l_shipdate >= DATE '1996-01-01'

        AND l_shipdate < DATE '1996-01-01' + INTERVAL '3' month

    GROUP BY

        l_suppkey;



-- The MATERIALIZED keyword is the trigger to begin

-- eagerly, consistently, and incrementally maintaining

-- results that are stored directly in durable storage.

CREATE MATERIALIZED VIEW tpch_q15 AS

  SELECT

    s_suppkey,

    s_name,

    s_address,

    s_phone,

    total_revenue

FROM

    supplier,

    revenue

WHERE

    s_suppkey = supplier_no

    AND total_revenue = (

        SELECT

            max(total_revenue)

        FROM

            revenue

    )

ORDER BY

    s_suppkey;



-- Creating an index keeps results always up to date and in memory.

-- In this example, the index will allow for fast point lookups of

-- individual supply keys.

CREATE INDEX tpch_q15_idx ON tpch_q15 (s_suppkey);

```



Stream inserts, updates, and deletes on the underlying tables (`lineitem` and `supplier`), and Materialize keeps the materialized view incrementally updated. You can type `SELECT * FROM tpch_q15` and expect to see the current results immediately!



## Get data out



**Pull based**: Use any PostgreSQL-compatible driver in any language/environment to make `SELECT` queries against your views. Tell them they're talking to a PostgreSQL database, they don't ever need to know otherwise.



**Push based**: Listen to changes directly using `SUBSCRIBE` or configure Materialize to stream results to a Kafka topic as soon as the views change.



## Documentation



Check out [our documentation](https://materialize.com/docs/).



## License



Materialize is provided primarily as a fully managed cloud service with

[credit-based pricing](https://materialize.com/pricing/). Included in the price

are proprietary cloud-native features like horizontal scalability, high

availability, and a web management console.



However, we're big believers in advancing the frontier of human knowledge. To

that end, the source code of the standalone database engine is publicly

available, in this repository, and [licensed](LICENSE) under the BSL 1.1,

converting to the open-source Apache 2.0 license after 4 years. As stated in the

BSL, use of the standalone database engine on a single node is free forever.

Please be warned that this deployment model is *not* suitable for production use

and we cannot offer support for it.



Materialize depends upon many open source Rust crates. We maintain a [list of

these crates and their licenses](https://dev.materialize.com/licenses.html),

including links to their source repositories.



## For developers



Materialize is primarily written in Rust.



Developers can find docs at [doc/developer](doc/developer), and Rust API documentation is hosted at .



Contributions are welcome. Prospective code contributors might find the [D-good

for external

contributors](https://github.com/MaterializeInc/materialize/discussions/categories/contribute-to-materialize?discussions_q=is%3Aopen+category%3A%22Contribute+to+Materialize%22+label%3A%22D-good+for+external+contributors%22)

discussion label useful. See

[CONTRIBUTING.md](https://github.com/MaterializeInc/materialize/blob/main/CONTRIBUTING.md)

for additional guidance.



## Credits



Materialize is lovingly crafted by [a team of developers](https://github.com/MaterializeInc/materialize/graphs/contributors) and one bot. [Join us](https://materialize.com/careers/).