Apache Arrow
Redis
Delta Lake
MongoDB
Apache Ignite
PostgreSQL
Apache Cassandra
Apache Parquet
Apache Pig
Looker
Jupyter
Presto DB
Google BigQuery
Databricks
Rakam
Informatica
Apache Arrow Apache PigBased on our record, Apache Arrow seems to be a lot more popular than Apache Pig. While we know about 34 links to Apache Arrow, we've tracked only 2 mentions of Apache Pig. 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.
Apache Doris 2.1 has a data transmission channel built on Arrow Flight SQL. (Apache Arrow is a software development platform designed for high data movement efficiency across systems and languages, and the Arrow format aims for high-performance, lossless data exchange.) It allows high-speed, large-scale data reading from Doris via SQL in various mainstream programming languages. For target clients that also... - Source: dev.to / 10 days ago
In comes Polars: a brand new dataframe library, or how the author Ritchie Vink describes it... a query engine with a dataframe frontend. Polars is built on top of the Arrow memory format and is written in Rust, which is a modern performant and memory-safe systems programming language similar to C/C++. - Source: dev.to / 3 months ago
One is related to the heritage of being built around the NumPy library, which is great for processing numerical data, but becomes an issue as soon as the data is anything else. Pandas 2.0 has started to bring in Arrow, but it's not yet the standard (you have to opt-in and according to the developers it's going to stay that way for the foreseeable future). Also, pandas's Arrow-based features are not yet entirely on... - Source: dev.to / 5 months ago
IMO a good first step would be to use the txr FFI to write a library for Apache arrow: https://arrow.apache.org/. - Source: Hacker News / 6 months ago
Polars is an open-source library for Python, Rust, and NodeJS that provides in-memory dataframes, out-of-core processing capabilities, and more. It is based on the Rust implementation of the Apache Arrow columnar data format (you can read more about Arrow on my earlier blog post “Demystifying Apache Arrow”), and it is optimised to be blazing fast. - Source: dev.to / about 1 year ago
Pig, a platform/programming language for authoring parallelizable jobs. - Source: dev.to / over 1 year ago
In the early days of the Big Data era when K8s hasn't even been born yet, the common open source go-to solution was the Hadoop stack. We have written several old-fashioned Map-Reduce jobs, scripts using Pig until we came across Spark. Since then Spark has became one of the most popular data processing engines. It is very easy to start using Lighter on YARN deployments. Just run a docker with proper configuration... - Source: dev.to / over 2 years ago
Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.
Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.
Delta Lake - Application and Data, Data Stores, and Big Data Tools
Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.
MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.
Presto DB - Distributed SQL Query Engine for Big Data (by Facebook)
