Security is emerging as a major priority for MarkLogic Corp. in its efforts to stand out amid fierce competition in the database market.
The company, which boasts Fortune 500 clients such as Johnson & Johnson Inc. and Deutsche Bank AG, today released a new version of its NoSQL store with a host of features for protecting sensitive information. The first enhancement is an expansion to the system’s access controls that introduces the ability to individually set usage restrictions for each element in a record. It comes just days after Neo Technology Inc., another major player in the NoSQL segment, added a similar capability to its graph database.
Both companies are hoping to hope large organizations where information is often shared among multiple teams with different security permissions. A bank, for instance, might want the ability to make client data available to its business analysts without exposing their credit card numbers. Such companies often also send records to third parties such as partners and regulators, a requirement that the new version of MarkLogic addresses as well.
The release brings a redaction feature that provides the ability to remove certain details from a dataset if it’s expected to end up somewhere with elevated privacy risks. That should be particularly useful for companies in regulated industries, which often have to go the extra mile when it comes to protecting user information.
The security enhancements in MarkLogic 9 are joined by a number of data management features designed to ease day-to-day operations. The arguably most notable is Entity Services, which provides the ability to organize information from different systems into a consistent model that captures the full picture. The feature lends itself to everything from creating customer profiles to centralizing different departmental records about an important transaction.
Entity Services expands upon MarkLogic’s set of features for importing and combining external information. The company claims that its system can help organizations consolidate data from disparate systems and analyze everything centrally, which can simplify analytics projects a great deal.