PolarDB-for-PostgreSQL
materialize
PolarDB-for-PostgreSQL | materialize | |
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13 | 117 | |
2,765 | 5,585 | |
0.6% | 0.8% | |
8.3 | 10.0 | |
10 days ago | 6 days ago | |
C | Rust | |
Apache License 2.0 | GNU General Public License v3.0 or later |
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PolarDB-for-PostgreSQL
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How to scale storage of PostgreSQL database?
Disaggregated storage for Postgres is still a very new technology, both with NeonDB and PolarDB (https://github.com/ApsaraDB/PolarDB-for-PostgreSQL).
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Neon – Serverless Postgres
Amazing work by the Team. Congrats y'all. It was one of the best presentations in the PGcon22.
I did email Heikki the following questions, in case if someone from Neon is around here.
a) How does Neon compare to polardb https://github.com/ApsaraDB/PolarDB-for-PostgreSQL.
b) The readme mentions a component "Repository - Neon storage implementation". Does it use any special FileSystem? Any links to read more about it?
c) Heard the cold start is a second (IIRC), how does that value differ if one runs Neon on bare metal instead of k8s?
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Start Your GitHub Journey From Contributing To Any GitHub Project
【Reference - Documentation】 https://github.com/alibaba/PolarDB-for-PostgreSQL#contributing
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[News] PolarDB for PostgreSQL Paxos Is Open Sourced
【GitHub - PolarDB for PostgreSQL】 Check Now >
- PolarDB, yet another open source database system based on PostgreSQL open-sourced by Alibaba
- alibaba/PolarDB-for-PostgreSQL - PolarDB, yet another open source database system based on PostgreSQL
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Hacker News top posts: May 30, 2021
PolarDB, yet another open source database system based on PostgreSQL\ (41 comments)
- PolarDB, yet another open source database system based on PostgreSQL
materialize
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Ask HN: How Can I Make My Front End React to Database Changes in Real-Time?
[2] https://materialize.com/
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Choosing Between a Streaming Database and a Stream Processing Framework in Python
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.
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Proton, a fast and lightweight alternative to Apache Flink
> 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
- What I Talk About When I Talk About Query Optimizer (Part 1): IR Design
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We Built a Streaming SQL Engine
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/
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Ask HN: Who is hiring? (October 2023)
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
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Investors include Redpoint, Lightspeed and Kleiner Perkins.
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Ask HN: Who is hiring? (June 2023)
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
- What are your favorite tools or components in the Kafka ecosystem?
- Ask HN: Who is hiring? (May 2023)
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Dozer: A scalable Real-Time Data APIs backend written in Rust
How does it compare to https://materialize.com/ ?
What are some alternatives?
citus - Distributed PostgreSQL as an extension
ClickHouse - ClickHouse® is a free analytics DBMS for big data
flyctl - Command line tools for fly.io services
risingwave - SQL stream processing, analytics, and management. We decouple storage and compute to offer speedy bootstrapping, dynamic scaling, time-travel queries, and efficient joins.
neon - Neon: Serverless Postgres. We separated storage and compute to offer autoscaling, branching, and bottomless storage.
openpilot - openpilot is an open source driver assistance system. openpilot performs the functions of Automated Lane Centering and Adaptive Cruise Control for 250+ supported car makes and models.
database-lab-engine - DBLab enables 🖖 database branching and ⚡️ thin cloning for any Postgres database and empowers DB testing in CI/CD. This optimizes database-related costs while improving time-to-market and software quality. Follow to stay updated.
rust-kafka-101 - Getting started with Rust and Kafka
helm-charts - neondatabase helm charts
dbt-expectations - Port(ish) of Great Expectations to dbt test macros
walex - Postgres change events (CDC) in Elixir
scryer-prolog - A modern Prolog implementation written mostly in Rust.