Apache Drill
materialize
Apache Drill | materialize | |
---|---|---|
9 | 117 | |
1,897 | 5,585 | |
1.1% | 0.8% | |
8.1 | 10.0 | |
6 days ago | 5 days ago | |
Java | Rust | |
Apache License 2.0 | 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.
Apache Drill
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Git Query Language (GQL) Aggregation Functions, Groups, Alias
Also are you familiar with apache drill . The idea is to put an SQL interpreter in front of any kind of database just like you are doing for git here.
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Building a Data Lakehouse for Analyzing Elon Musk Tweets using MinIO, Apache Airflow, Apache Drill and Apache Superset
💡 You ca read more here.
- 【上海报案信息】高频关键词 (OC)
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DeWitt Clause, or Can You Benchmark %DATABASE% and Get Away With It
Apache Drill, Druid, Flink, Hive, Kafka, Spark
- 说的都是什么傻逼东西,一堆警察等了一小时不敢进去还他妈怪拜登不让学校有持枪警卫?哪个财团大得过控制整个共和党的NRA?
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Apache Drill: the reports of my death have been greatly exaggerated
>We’ve started talking about speeding up our release cadence to better reflect our recent activity.
There's been only one release per year in the past so you can't fault anyone to think the project is dead.
https://github.com/apache/drill/releases
- Concept: A open source alternative to big query ?
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Roapi: An API Server for Static Datasets
Looks super interesting and potentially useful. Curious how it compares with Apache Drill (https://drill.apache.org/).
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Does Java have an open source package that can execute SQL on txt/csv?
Check out Apache Drill: https://drill.apache.org/
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?
Trino - Official repository of Trino, the distributed SQL query engine for big data, formerly known as PrestoSQL (https://trino.io)
ClickHouse - ClickHouse® is a free analytics DBMS for big data
Apache Calcite - Apache Calcite
risingwave - SQL stream processing, analytics, and management. We decouple storage and compute to offer speedy bootstrapping, dynamic scaling, time-travel queries, and efficient joins.
Presto - The official home of the Presto distributed SQL query engine for big data
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.
AranoDB - The official ArangoDB Java driver.
rust-kafka-101 - Getting started with Rust and Kafka
QueryStream - Build JPA Criteria queries using a Stream-like API
dbt-expectations - Port(ish) of Great Expectations to dbt test macros
spring-data-jpa-mongodb-expressions - Use the MongoDB query language to query your relational database, typically from frontend.
scryer-prolog - A modern Prolog implementation written mostly in Rust.