Apache HBase VS Apache Arrow

HBase and Cassandra: Both cater to non-structured Big Data. Cassandra is geared towards scenarios requiring high availability with eventual consistency, while HBase offers strong consistency and is better suited for read-heavy applications where data consistency is paramount. - Source: dev.to / 2 months ago

NoSQL databases are non-relational databases with flexible schema designed for high performance at a massive scale. Unlike traditional relational databases, which use tables and predefined schemas, NoSQL databases use a variety of data models. There are 4 main types of NoSQL databases - document, graph, key-value, and column-oriented databases. NoSQL databases generally are well-suited for unstructured data,... - Source: dev.to / 10 months ago

HBase, A scalable, distributed database that supports structured data storage for large tables. - Source: dev.to / over 1 year ago

Today, it is normal for enterprises to leverage diversified databases. In my market of expertise, China, in the Internet industry, MySQL together with data sharding middleware is the go to architecture, with GreenPlum, HBase, Elasticsearch, Clickhouse and other big data ecosystems being auxiliary computing engine for analytical data. At the same time, some legacy systems (such as SQLServer legacy from .NET... - Source: dev.to / almost 2 years ago

For this type of systems PostgreSQL not best solution, and for a number of reasons like lack of replication out of the box. And we strictly must not have «Vendor lock», and therefore also did not take modern SQL databases like Amazon Aurora. And end of the ends the choice was made in favor Cassandra, for this article where we will talking about low-lever implementation of Repository Pattern it is not important, in... - Source: dev.to / about 2 years 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 / about 2 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 / 5 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 / 12 months ago

Apache Arrow (Arrow for short) is an open source project that defines itself as "a language-independent columnar memory format" (more on that later). It is part of the Apache Software Foundation, and as such is governed by a community of several stakeholders. It has implementations in several languages (C++ and also Rust, Julia, Go, and even JavaScript) and bindings for Python, R and others that wrap the C++... - Source: dev.to / 12 months ago