From Amazon to Splunk, here's a look at the big data innovators that are now pushing Hadoop, NoSQL and big data analytics to the next level.
Hadapt was hip to the need for business intelligence and analytics on top of Hadoop before its first round of funding in early 2011. Hive, the Apache data warehousing component that runs on top of Hadoop, relies on slow, batch-oriented MapReduce processing. Hadapt works around that delay by adding a hybrid storage layer to Hadoop that provides relational data access. From there you can do SQL-based analysis of massive data sets using SQL-like Hadapt Interactive Query. The software automatically splits query execution between the Hadoop and relational database layers, delivering the speed of relational tools with the scalability of Hadoop. There's also a development kit for creating custom analytics, and you can work with popular, relational-world tools such as Tableau software.
Hadapt is in good company, with Cloudera (Impala), Datameer, Karmasphere, Platfora and others all working on various ways to meet the same analytics-on-Hadoop challenge. It remains to be seen which of these vendors will be a breakout success in 2013.
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Amazon Debuts Low-Cost, Big Data Warehousing Service
Cloudera Debuts Real-Time Hadoop Query
Big Data Analytics Challenges Old-School Business Intelligence
Why Sears Is Going All-In On Hadoop
MapR Promises A Better Hbase
Hadoop Meets Near Real-Time Data
MapR's Google Deal Marks Second Big Data Cloud Win
Sears Hadoop Plans: Check Out Data Warehousing's Future
Splunk Answers Business Demand For Big Data Analysis