Big Data Technologies

The Big Data Technologies Map aims to visualize the big data ‘on-premise’ technologies in one place – open source and proprietary licensed together.
The map is divided into 5 categories – Data Repositories, Data Analysis, Development Frameworks, Real-Time Computation, In-Memory Data Grids and Middleware.

• Data Repositories – The foundation of the Big Data world, for many this category is what Big Data is all about – Hadoop, NoSQLs, Analytic Databases and more. Nevertheless, as important as this category is, it’s only one part of the the entire puzzle.
• Data Analysis – This category consists of different solutions for data analysis and visualization: from classic BI tools adjusting their capabilities to new agile tools solving niche problems such as log analysis; sophisticated data visualization libraries and more.
• Development Frameworks – MapReduce, Hive, Pig, etc.. everything you need to know in order to start developing big data products.
• Real Time Computation – The rise of Real Time Web is driving new technologies that can handle large amount of traffic and provide real time analysis and computation of that data.
• In-Memory Data Grids – These tools provide a fabric of servers maintaining an in-memory cache of data enabling quick response to queries without the need to access a data repository for every request.
• Middleware – tools that glue everything together, while they rarely provide real business on their own, they are in many cases necessary to make a system work smoothly.

Not all is black and white, feel free to comment on any inaccuracies and/or additions below…