awesome-bigdata README

The project's README from github.com/oxnr/awesome-bigdata. As one markdown file: README.md.

Awesome Big Data

Awesome

A curated list of awesome big data frameworks, resources and other awesomeness. Inspired by awesome-php, awesome-python, awesome-ruby, hadoopecosystemtable & big-data.

Your contributions are always welcome!

RDBMS

Frameworks

Distributed Programming

Distributed Filesystem

Distributed Index

Document Data Model

Key Map Data Model

Note: There is some term confusion in the industry, and two different things are called "Columnar Databases". Some, listed here, are distributed, persistent databases built around the "key-map" data model: all data has a (possibly composite) key, with which a map of key-value pairs is associated. In some systems, multiple such value maps can be associated with a key, and these maps are referred to as "column families" (with value map keys being referred to as "columns").

Another group of technologies that can also be called "columnar databases" is distinguished by how it stores data, on disk or in memory -- rather than storing data the traditional way, where all column values for a given key are stored next to each other, "row by row", these systems store all column values next to each other. So more work is needed to get all columns for a given key, but less work is needed to get all values for a given column.

The former group is referred to as "key map data model" here. The line between these and the Key-value Data Model stores is fairly blurry.

The latter, being more about the storage format than about the data model, is listed under Columnar Databases.

You can read more about this distinction on Prof. Daniel Abadi's blog: Distinguishing two major types of Column Stores.

Key-value Data Model

Graph Data Model

Columnar Databases

Note please read the note on Key-Map Data Model section.

NewSQL Databases

Time-Series Databases

Lakehouse Table Formats

SQL-like processing

Vector Databases

Data Ingestion

Data Quality and Observability

Service Programming

Scheduling

Machine Learning

Benchmarking

Security

System Deployment

Applications

Search engine and framework

MySQL forks and evolutions

PostgreSQL forks and evolutions

Memcached forks and evolutions

Embedded Databases

Business Intelligence

Data Visualization

Internet of things and sensor data

Interesting Readings

Interesting Papers

2015 - 2016

2013 - 2014

2011 - 2012

2001 - 2010

Videos

Books

Streaming

Distributed systems

Graph Based approach

Data Visualization

Other Awesome Lists

awesome-bigdata (oxnr/awesome-bigdata)

Searching Database…

这是什么?这是一份精选列表,收录与大数据相关的框架、数据库、工具、论文和资源,涵盖从分布式处理引擎到键值存储、可视化工具等内容。
这是一个工具,还是只是一份链接列表?它纯粹是一个 markdown 索引,收录指向外部项目和论文的链接,并按 RDBMS、分布式编程、分布式文件系统和数据模型等分类组织。
这份列表是怎么组织的?条目按分类分组,例如 RDBMS、Frameworks、分布式编程、分布式文件系统、键值与列式数据模型、数据采集、机器学习、安全、商业智能等,每个条目都附有简短说明。
新手应该从哪里开始?由于这是一份参考列表而非软件,新手可以先从 RDBMS 或 Frameworks 部分入手,了解 MySQL、PostgreSQL、Apache Hadoop 等基础工具,然后再探索更专门的分类。
条目经过审核,还是仍在更新?该列表创建于 2014 年,收录的多为较早的框架和论文(时间可追溯到 2001 至 2016 年),因此较新的大数据工具可能未被收录,部分已列出的项目可能已过时或被弃用。
这只涉及处理框架,还是也包括数据库?两者都涵盖:既有分布式处理引擎(Hadoop、Spark、Flink、Storm),也有大量数据库,涵盖文档型、键值型、列式、图、时序和 NewSQL 等数据模型。
除了工具链接,它还包含学习资源吗?包含。除工具列表外,还设有精选阅读、精选论文(按年份组织)、视频和书籍等专门部分。
为什么要创建这份列表?它受到其他 awesome 风格精选列表(awesome-php、awesome-python、awesome-ruby)以及 Hadoop 生态系统表格的启发,旨在成为大数据领域的全面参考。
Creator
oxnr
Size
1 MB
Stars
14.7K
Updated
CommitJul 31
Age
12y
Commits · 90 Days