Mcafee bad catalog when updating

In 2010, it became clear that Mc Afee’s existing database solutions would not be able to handle the demands of exponential data growth.The team spent a significant amount of time investigating workarounds and fixes, which created new cracks in the system.Mc Afee turned to Mongo DB to achieve the scale, performance and flexibility required for big data analysis.Mc Afee GTI analyzes cyberthreats from all angles, identifying threat relationships, such as malware used in network intrusions, websites hosting malware, botnet associations, and more.Mongo DB offers the flexibility to store different types of documents in a single collection.

This means that no matter what application language Mc Afee chooses to use for a project, they know interfacing with Mongo DB will be a snap.what domain the IP address is associated with, who it’s talked to, whether who it’s talked to is known good or bad – a “forest of information” that enables GTI to develop meaningful relationships with several different schema.“Instead of fitting the problem to the tool, Mongo DB is able to morph to any problem, so thinking about the problem is a lot simpler,” said Widner.Developers can change the database’s schema at any time, shortening development cycles and dramatically increasing productivity.Threat information is extremely time sensitive; knowing about a threat from weeks ago is useless. The success of the cloud-based system also depends on a bidirectional data flow: GTI gathers data from millions of client sensors and provides real-time intelligence back to these end products, at a rate of 100 billion queries per month.In order to provide up to date, comprehensive threat information, Mc Afee needs to quickly process terabytes of different data types (such as IP address or domain) into meaningful relationships: e.g. Mc Afee was unable to address these needs and effectively scale out to millions of records with their existing solutions.

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