materialize
sourcegraph
materialize | sourcegraph | |
---|---|---|
117 | 69 | |
5,580 | 9,726 | |
0.7% | 1.0% | |
10.0 | 10.0 | |
4 days ago | 7 days ago | |
Rust | Go | |
GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
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/ ?
sourcegraph
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Ask HN: Who is hiring? (March 2024)
Sourcegraph | REMOTE | Full-Time | Machine Learning Engineer, Developer Advocate, Enterprise Product Manager, Technical Advisor | https://sourcegraph.com
Sourcegraph is a code AI platform that makes it easy to read, write, and fix code–even in big, complex codebases.
We are building Cody, an AI coding assistant that uses code search and code intelligence to help devs quickly understand what's happening in code and generate new code that matches the best practices in your codebase. Cody supports AI-enabled autocompletion, fixing bugs, refactoring, test generation, code explanation, and answering high-level questions. You can read Steve Yegge's post on why Cody's code context engine differentiates it from the fast-moving field of AI dev tools: https://about.sourcegraph.com/blog/cheating-is-all-you-need.
Apply here: https://grnh.se/0572f98b4us
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Architecture.md (2021)
That's pretty much what https://sourcegraph.com/ are selling, is it not?
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Tell HN: GitHub is blocking search unless you are logged in
Despite their shitty rug-pull <https://github.com/sourcegraph/sourcegraph/pull/53345>, I do really like Sourcegraph and one doesn't (currently?!) need to be logged in to use it: https://sourcegraph.com/search and they have a handy rewrite pattern such that one can just plug the repo path into the URL for quick searching e.g. https://sourcegraph.com/github.com/JetBrains/intellij-commun...
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My 2024 AI Predictions
- https://sourcegraph.com is pivoting and building a copilot application (named Cody). This is pretty good, since sourcegraph is great at understanding your code
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The Curse of Docker
While a readable Dockerfile can work as documentation, there are a few caveats:
* the application needs to be designed to work outside containers (so, no hardcoded URLs, ports, or paths). Also, not directly related to containers, but it's nice if it can be easily compiled in most environments and not just on the base image.
* I still need a way to notify me of updates; if the Dockerfile just wgets a binary, this doesn't help me.
* The Dockerfiles need to be easy to find. Sourcegraph's don't seem to be referenced from the documentation, I had to look through their Github repos to find https://github.com/sourcegraph/sourcegraph/tree/main/docker-... (though most are bazel scripts instead of Dockerfiles, but serve the same purpose)
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Building Reddit’s Design System on iOS
We use Sourcegraph, which is a tool that searches through code in repositories. We leverage this tool in order to understand the adoption curve of our components across all of Reddit. We have a dashboard for each of the platforms to compare the inclusion of RPL components over legacy components. These insights are helpful for us to make informed decisions on how we continue to drive RPL adoption. We love seeing the green line go up and the red line go down!
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Launch HN: GitStart (YC S19) – Remote junior devs working on production PRs
SourceGraph: https://github.com/sourcegraph/sourcegraph/pulls?q=is%3Apr+a...
- Sourcegraph is no longer Open Source
What are some alternatives?
ClickHouse - ClickHouse® is a free analytics DBMS for big data
opengrok - OpenGrok is a fast and usable source code search and cross reference engine, written in Java
risingwave - SQL stream processing, analytics, and management. PostgreSQL simplicity, unrivaled performance, and seamless elasticity. 🚀 10x more productive. 🚀 10x more cost-efficient.
tree-sitter - An incremental parsing system for programming tools
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.
Code-Server - VS Code in the browser
rust-kafka-101 - Getting started with Rust and Kafka
theia-apps - Theia applications examples - docker images, desktop apps, packagings
dbt-expectations - Port(ish) of Great Expectations to dbt test macros
Vue Storefront - Alokai is a Frontend as a Service solution that simplifies composable commerce. It connects all the technologies needed to build and deploy fast & scalable ecommerce frontends. It guides merchants to deliver exceptional customer experiences quickly and easily.
scryer-prolog - A modern Prolog implementation written mostly in Rust.
Atheos - A self-hosted browser-based cloud IDE, updated from Codiad IDE