Apache Arrow
Redis
Apache Parquet
DuckDB
Apache Spark
Pandas
KeyDB
ClickHouse
OctoSQL
Materialize
LNAV
Steampipe
DuckDB
RisingWave
Frame
DSQ
Apache Arrow OctoSQLNo OctoSQL videos yet. You could help us improve this page by suggesting one.
Based on our record, Apache Arrow should be more popular than OctoSQL. It has been mentiond 40 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
I had no idea what Arrow is: https://arrow.apache.org or arrow-rs: https://github.com/apache/arrow-rs. - Source: Hacker News / about 2 months ago
- Open source: Pontoon is free to use by anyone Under the hood, we use Apache Arrow (https://arrow.apache.org/) to move data between sources and destinations. Arrow is very performant - we wanted to use a library that could handle the scale of moving millions of records per minute. In the shorter-term, there are several improvements we want to make, like:. - Source: Hacker News / 2 months ago
Apache Arrow : It contains a set of technologies that enable big data systems to process and move data fast. - Source: dev.to / 10 months ago
One of the main selling points of Polars over similar solutions such as Pandas is performance. Polars is written in highly optimized Rust and uses the Apache Arrow container format. - Source: dev.to / 11 months ago
Kotlin DataFrame v0.14 comes with improvements for reading Apache Arrow format, especially loading a DataFrame from any ArrowReader. This improvement can be used to easily load results from analytical databases (such as DuckDB, ClickHouse) directly into Kotlin DataFrame. - Source: dev.to / over 1 year ago
This looks extremely cool. This is basically incremental view maintenance in databases, a problem that almost everybody (I think) has when using SQL databases and wanting to do some derived views for more performant access patterns. Importantly, they seem to support a wide breath of SQL operators, and it's open-source! There's already a bunch of tools in this area: 1. Materialize[0], which afaik is more... - Source: Hacker News / about 1 year ago
OctoSQL[0] or DuckDB[1] will most likely be much simpler, while going through 10 GB of JSON in a couple seconds at most. Disclaimer: author of OctoSQL [0]: https://github.com/cube2222/octosql. - Source: Hacker News / over 2 years ago
This is really cool! With their Postgres scanner[0] you can now easily query multiple datasources using SQL and join between them (i.e. Postgres table with JSON file). Something I strived to build with OctoSQL[1] before. It's amazing to see how quickly DuckDB is adding new features. Not a huge fan of C++, which is right now used for authoring extensions, it'd be really cool if somebody implemented a Rust extension... - Source: Hacker News / over 2 years ago
Congrats on the Show HN! It's great to see more tools in this area (querying data from various sources in-place) and the Lambda use case is a really cool idea! I've recently done a bunch of benchmarking, including ClickHouse Local and the usage was straightforward, with everything working as it's supposed to. Just to comment on the performance area though, one area I think ClickHouse could still possibly improve... - Source: Hacker News / over 2 years ago
SPyQL is really cool and its design is very smart, with it being able to leverage normal Python functions! As far as similar tools go, I recommend taking a look at DataFusion[0], dsq[1], and OctoSQL[2]. DataFusion is a very (very very) fast command-line SQL engine but with limited support for data formats. Dsq is based on SQLite which means it has to load data into SQLite first, but then gives you the whole breath... - Source: Hacker News / almost 3 years ago
Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.
Materialize - A Streaming Database for Real-Time Applications
Apache Parquet - Apache Parquet is a columnar storage format available to any project in the Hadoop ecosystem.
LNAV - The Log File Navigator (lnav) is an advanced log file viewer for the console.
DuckDB - DuckDB is an in-process SQL OLAP database management system
Steampipe - Steampipe: select * from cloud; The extensible SQL interface to your favorite cloud APIs select * from AWS, Azure, GCP, Github, Slack etc.
