quine
materialize
quine | materialize | |
---|---|---|
6 | 120 | |
283 | 5,598 | |
3.9% | 1.0% | |
9.4 | 10.0 | |
6 days ago | 6 days ago | |
Scala | Rust | |
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.
quine
-
Create a Quine Icon Library with Python
Quine
-
Postgres: The Graph Database You Didn't Know You Had
Re [5]'s asssertion under "blunders" of the diminish usecases post sql/pgq, what do you think of sometime like Quine?
https://github.com/thatdot/quine
Their claim to fame is progressive incremental computation - each node is an actor responding to events -- and I'm not sure how a relational db could do that and match the latencies. That usecase is pretty much pattern matching and forensics and stuff like that.
https://docs.quine.io/core-concepts/architecture.html
-
Use Quine Graph ETL to reduce SIEM storage costs.
Download Quine - JAR file | Docker Image | Github
-
Standing Queries: Turning Data-Driven Events into Event-Driven Data
The first step to making a Standing Query is determining the graph pattern you want to watch for. You may have deployed Quine in your data pipeline to perform a series of tasks to isolate data, implement a specific feature, or monitor the stream to find a specific pattern in real time. In any case, Quine will implement your logic using Cypher. The recipe for this example is included in the Quine repo if you'd like to follow along.
-
Ingesting From Multiple Data Sources into Quine Streaming Graphs
Quine is open source if you want to run this analysis for yourself. Download a precompiled version or build it yourself from the codebase (Quine Github). I published the recipe that I developed at https://quine.io/recipes. The page has instructions for downloading the CSV files and running the recipe.
-
Ingesting Internet Data into Quine Streaming Graph
I welcome your feedback! Drop in to Quine Slack and let me know what you think. I'm always happy to discuss Quine or answer questions.
materialize
-
Ask HN: How Can I Make My Front End React to Database Changes in Real-Time?
[2] https://materialize.com/
-
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.
-
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
-
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/
-
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
===
Investors include Redpoint, Lightspeed and Kleiner Perkins.
-
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)
-
Dozer: A scalable Real-Time Data APIs backend written in Rust
How does it compare to https://materialize.com/ ?
What are some alternatives?
lila-ws - Lichess' websocket server
ClickHouse - ClickHouse® is a free analytics DBMS for big data
AkkaGRPC - Akka gRPC
risingwave - SQL stream processing, analytics, and management. We decouple storage and compute to offer instant failover, dynamic scaling, speedy bootstrapping, and efficient joins.
Scala Graph - Graph for Scala is intended to provide basic graph functionality seamlessly fitting into the Scala Collection Library. Like the well known members of scala.collection, Graph for Scala is an in-memory graph library aiming at editing and traversing graphs, finding cycles etc. in a user-friendly way.
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.
fs2-kafka - Functional Kafka Streams for Scala
rust-kafka-101 - Getting started with Rust and Kafka
Iteratee - Iteratees for Cats
dbt-expectations - Port(ish) of Great Expectations to dbt test macros
ldbc_snb_bi - Reference implementations for the LDBC Social Network Benchmark's Business Intelligence (BI) workload
scryer-prolog - A modern Prolog implementation written mostly in Rust.