materialize
delta-rs
materialize | delta-rs | |
---|---|---|
120 | 28 | |
5,627 | 1,897 | |
1.0% | 4.1% | |
10.0 | 9.7 | |
about 19 hours ago | 7 days ago | |
Rust | Rust | |
GNU General Public License v3.0 or later | Apache License 2.0 |
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
-
The Notifier Pattern for Applications That Use Postgres
Those updates are not retroactive. They apply on a go forward basis. Each day's changes become Apache 2.0 licensed on that day four years in the future.
For example, v0.28 was released on October 18, 2022, and becomes Apache 2.0 licensed four years after that date (i.e., 2.5 years from today), on October 18, 2026.
[0]: https://github.com/MaterializeInc/materialize/blob/76cb6647d...
-
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)
delta-rs
- Delta-rs – a Rust-based implementation of deltalake
-
Delta Lake vs. Parquet: A Comparison
I work at Databricks, but am pretty must just an OSS nerd, mainly focusing on Delta Rust recently: https://github.com/delta-io/delta-rs
I did some keyword research and wrote this post cause lots of folks are doing searches for Delta Lake vs Parquet. I'm just trying to share a fair summary of the tradeoffs with folks who are doing this search. It's a popular post and that's why I figured I would share it here.
-
Working with Rust
Seeing a lot of great libraries coming out with python bindings in the data world e.g delta-rs Polars. I see it growing in this space as a C++ alternative
-
Ideas/Suggestions around setting up a data pipeline from scratch
If I’m not misunderstanding, you could both decode the gRPC protobuf AND write to delta lake in Rust. Tonic, Delta-rs.
-
Delta-rs with upserts
https://github.com/delta-io/delta-rs/issues/850 … looks like it’s on the roadmap!
-
Read and filter delta files on Azure from a .net application
Microsoft talk a lot about OneLake and that the delta file format will be the standard during the build conference. Is it only me that find it strange that their marketing team talks so much about the delta format when they do not even provide a library to work with the delta format from .net? It would be easy for them to maintain bindings to https://github.com/delta-io/delta-rs but also provide a reader that support V-Order https://learn.microsoft.com/en-us/fabric/data-engineering/delta-optimization-and-v-order?tabs=sparksql
-
Polars query engine 0.29.0 released
I know someone will be adding this on the python side in the coming weeks. On the rust side you can use delta-rs with polars. Though you would be compiling both arrow2 and arrow-rs, so that's quite heavy.
-
Delta Lake without Databricks?
You don’t need DBX to use Delta Lake. You can use S3 as the backend and just use the Python Delta Lake library. It works great! https://github.com/delta-io/delta-rs
-
Seeking Recommendations for a Master Data Management Tool
Maybe if I get some free time soon I can formalize into a working example. Been wanting an excuse to try similar concept in delta-rs and polars/duckdb vs databricks/spark vs iceberg/polars.
-
Opportunity to contribute to a popular Rust data project (delta-rs)
delta-rs is a native Rust library for Delta Lake. It's a better way to store data than Parquet files and is fundamentally important library for the Rust data ecosystem. It's tightly integrated with Polars and Datafusion and there is a lot of interesting Rust work to be done.
What are some alternatives?
ClickHouse - ClickHouse® is a real-time analytics DBMS
delta - An open-source storage framework that enables building a Lakehouse architecture with compute engines including Spark, PrestoDB, Flink, Trino, and Hive and APIs
risingwave - SQL stream processing, analytics, and management. We decouple storage and compute to offer instant failover, dynamic scaling, speedy bootstrapping, and efficient joins.
roapi - Create full-fledged APIs for slowly moving datasets without writing a single line of code.
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.
ballista - Distributed compute platform implemented in Rust, and powered by Apache Arrow.
rust-kafka-101 - Getting started with Rust and Kafka
kafka-delta-ingest - A highly efficient daemon for streaming data from Kafka into Delta Lake
dbt-expectations - Port(ish) of Great Expectations to dbt test macros
delta-oss
scryer-prolog - A modern Prolog implementation written mostly in Rust.
polars - Dataframes powered by a multithreaded, vectorized query engine, written in Rust