With Storm and Kafka, you can conduct stream processing at linear scale, assured that every message gets processed in real-time, reliably. In tandem, Storm and Kafka can handle data velocities of tens of thousands of messages every second.Extrémním tempem nepřibývá jen dat, ale také technologií, které je umožňují zpracovat. Těch několik, jež jmenuje citovaný článek, patří mezi klíčové a budeme se jimi zde postupně zabývat podrobněji.
Stream processing solutions like Storm and Kafka have caught the attention of many enterprises due to their superior approach to ETL (extract, transform, load) and data integration.
(...) Drill and Dremel compare favorably to Hadoop for anything ad-hoc. Hadoop is all about batch processing workflows, which creates certain disadvantages.
(...) R is an open source statistical programming language. It is incredibly powerful. Over two million (and counting) analysts use R. It’s been around since 1997 if you can believe it. It is a modern version of the S language for statistical computing that originally came out of the Bell Labs. Today, R is quickly becoming the new standard for statistics.
(...) Gremlin and Giraph help empower graph analysis, and are often used coupled with graph databases like Neo4j or InfiniteGraph, or in the case of Giraph, working with Hadoop. Golden Orb is another high-profile example of a graph-based project picking up steam. Graph databases are pretty cutting edge. They have interesting differences with relational databases, which mean that sometimes you might want to take a graph approach rather than a relational approach from the very beginning.
(...) SAP Hana is an in-memory analytics platform that includes an in-memory database and a suite of tools and software for creating analytical processes and moving data in and out, in the right formats.
Tim Gasper, TechCrunch: Big Data Right Now: Five Trendy Open Source Technologies