store VS materialize

Cool! I do this, but I haven't seen anyone else do it. Is any of your code public?

I wrote about it at https://sive.rs/pg

and posted my SQL shopping cart at https://github.com/sivers/store

Please contact me if you'd like to share tips: https://sive.rs/contact

Also:

https://sive.rs/pg2 - Simplify: move code into database functions

https://sive.rs/pg - PostgreSQL example of self-contained stored procedures

some linked examples: https://github.com/sivers/store/tree/master/store/functions

I like this idea in theory ... although it would cause me to need to know a lot more SQL, which is a powerful but hostile language :-/

I care about factoring stuff out into expressions / functions and SQL fails in that regard ...

https://www.scattered-thoughts.net/writing/against-sql/

It's hard to imagine doing this with a ton of duplication. I have written SQL by hand and there are probably more confusing corners than shell, which is saying a lot (and which I didn't have too hard a time learning)

[2] https://materialize.com/

To fully leverage the data is the new oil concept, companies require a special database designed to manage vast amounts of data instantly. This need has led to different database forms, including NoSQL databases, vector databases, time-series databases, graph databases, in-memory databases, and in-memory data grids. Recent years have seen the rise of cloud-based streaming databases such as RisingWave, Materialize, DeltaStream, and TimePlus. While they each have distinct commercial and technical approaches, their overarching goal remains consistent: to offer users cloud-based streaming database services.

> Materialize no longer provide the latest code as an open-source software that you can download and try. It turned from a single binary design to cloud-only micro-service

Materialize CTO here. Just wanted to clarify that Materialize has always been source available, not OSS. Since our initial release in 2020, we've been licensed under the Business Source License (BSL), like MariaDB and CockroachDB. Under the BSL, each release does eventually transition to Apache 2.0, four years after its initial release.

Our core codebase is absolutely still publicly available on GitHub [0], and our developer guide for building and running Materialize on your own machine is still public [1].

It is true that we substantially rearchitected Materialize in 2022 to be more "cloud-native". Our new cloud offering offers horizontal scalability and fault tolerance—our two most requested features in the single-binary days. I wouldn't call the new architecture a microservices design though! There are only 2-3 services, each quite substantial, in the new architecture (loosely: a compute service, an orchestration service, and, soon, a load balancing service).

We do push folks to sign up for a free trial of our hosted cloud offering [2] these days, rather than trying to start off by running things locally, as we generally want folks' first impression of Materialize to be of the version that we support for production use cases. A all-in-one single machine Docker image does still exist, if you know where to look, but it's very much use-at-your-own-risk, and we don't recommend using it for anything serious, but it's there to support e.g. academic work that wants to evaluate Materialize's capabilities to incrementally maintain recursive SQL queries.

If folks have questions about Materialize, we've got a lively community Slack [3] where you can connect directly with our product and engineering teams.

[0]: https://github.com/MaterializeInc/materialize/tree/main

Some recent solutions to this problem include Differential Dataflow and Materialize. It would be neat if postgres adopted something similar for live-updating materialized views.

https://github.com/timelydataflow/differential-dataflow

https://materialize.com/

Materialize | Full-Time | NYC Office or Remote | https://materialize.com

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. Keep the familiar SQL, keep the proven architecture of cloud warehouses but swap the decades-old batch computation model for an efficient incremental engine to get complex queries that are always up-to-date.

Materialize is the operational data warehouse built from the ground up to meet the needs of modern data products: Fresh, Correct, Scalable — all in a familiar SQL UI.

Senior/Staff Product Manager - https://grnh.se/69754ebf4us

Senior Frontend Engineer - https://grnh.se/7010bdb64us

===

Investors include Redpoint, Lightspeed and Kleiner Perkins.

Materialize | EM (Compute), Senior PM | New York, New York | https://materialize.com/

You shouldn't have to throw away the database to build with fast-changing data. Keep the familiar SQL, keep the proven architecture of cloud warehouses, but swap the decades-old batch computation model for an efficient incremental engine to get complex queries that are always up-to-date.

That is Materialize, the only true SQL streaming database built from the ground up to meet the needs of modern data products: Fresh, Correct, Scalable — all in a familiar SQL UI.

Engineering Manager, Compute - https://grnh.se/4e14099f4us

Senior Product Manager - https://grnh.se/587c36804us

VP of Marketing - https://grnh.se/9caac4b04us

How does it compare to https://materialize.com/ ?