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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Neo Technology Database Manages Social Relationships "Social applications and graph databases go together like peanut butter and jelly," says graph database consultant Max De Marzi. That's the big reason Neo4j, the open source graph database developed and supported by Neo Technologies, has a unique place in the NoSQL world.
Neo4j is used to model and query highly complex interconnected networks with an ease that's not possible with relational databases or other NoSQL products. Other NoSQL databases may excel in dealing with ever-changing data, but graph databases shine in dealing with ever-evolving relationships. In social network applications you can model and query the ever-changing social graph. In IT and telecom network scenarios you can quickly resolve secure access challenges. In master data management applications you can see changing relationships among data. And in recommendation-engine apps you can figure out what people want before they know they want it.
Neo4j is a general-purpose graph database that can handle transaction processing or analytics, and it's compatible with leading development platforms including Java, Ruby, Python, Groovy and others. Neo Technology is working on scale-out architecture, but even without that, Neo4j can manage and reveal billions of relationships. As social and network applications multiply, Neo Technology is in a prime position to manage the future.
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?