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.
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Hadapt Brings Relational Analytics To Hadoop 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.
6 Tools to Protect Big DataMost IT teams have their conventional databases covered in terms of security and business continuity. But as we enter the era of big data, Hadoop, and NoSQL, protection schemes need to evolve. In fact, big data could drive the next big security strategy shift.
Big Data Brings Big Security ProblemsWhy should big data be more difficult to secure? In a word, variety. But the business wonít wait to use it to predict customer behavior, find correlations across disparate data sources, predict fraud or financial risk, and more.