Apache Arrow
Redis
Delta Lake
MongoDB
Apache Ignite
PostgreSQL
Apache Cassandra
Apache Parquet
QualCoder
MAXQDA
ATLAS.ti
NVivo
Taguette
RQDA
Quirkos
Dedoose
QualCoder is free, open source software for qualitative data analysis. You can code text, images, audio and video, write journal notes and memos. Categorise codes in a tree-like hierarchical categorisation scheme. Coding for audio and video requires the VLC media player. VLC must be installed for QualCoder to work. Coder comparison reports can be generated for text coding. A graph displaying codes and categories can be generated to visualise the coding hierarchy. Most reports can be exported at html, open document text (ODT) or as plain text files.
Apache Arrow QualCoderQualCoder is one of the best CAQDAS I have used not just because it is free and open source but also because of the functionalities and constant improvements.
I really like using QualCoder 3.0 for its ease of use and intuitive interface.
The software is efficient and powerful to perform the content analysis task. It allows you to follow the categories and classifications clearly. Facilitates thematic analysis. It is an excellent technology to implement a qualitative methodology. It is a 100% recommended software.
Based on our record, Apache Arrow seems to be more popular. It has been mentiond 34 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.
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 / 20 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 / 6 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
Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.
MAXQDA - a professional software for qualitative and mixed methods data analysis
Delta Lake - Application and Data, Data Stores, and Big Data Tools
ATLAS.ti - ATLAS.ti is a powerful workbench for the qualitative analysis of large bodies of textual, graphical, audio and video data. It offers a variety of sophisticated tools for accomplishing the tasks associated with any systematic approach to "soft" data.
MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.
NVivo - Buy NVivo now for flexible solutions to meet your specific research and data analysis needs.
