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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10Gen Scales Up Developer-Friendly Mongo DB 10Gen is the developer and commercial support provider behind open source MongoDB. Among six NoSQL databases highlighted in this roundup (along with DynamoDB, Cassandra, HBase, CouchBase and Neo Technologies), MongoDB is distinguished as the leading document-oriented database. As such it can handle semi-structured information encoded in JSON (Java Script Object Notation), XML or other document formats. The big attraction is flexibility, speed and ease of use, as you can quickly embrace new data without the rigid schemas and data transformations required by relational databases.
MongoDB is not the scalability champion of the NoSQL set, but 10Gen is working on that. In 2012 it introduced MongoDB 2.2, which added a real-time aggregation framework, new sharding and replication features for multi-data center deployments, and improved performance and database concurrency for high-scale deployments. The data aggregation framework fills an analytics void by letting users directly query data within MongoDB without using complicated batch-oriented MapReduce jobs. CouchBase plans to step up competition with MongoDB by way of JSON support, but we're sure 10Gen and the MongoDB community will step up to improve scalability and performance 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.
InformationWeek Tech Digest, Nov. 10, 2014Just 30% of respondents to our new survey say their companies are very or extremely effective at identifying critical data and analyzing it to make decisions, down from 42% in 2013. What gives?