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Best Practices for NoSQL Databases

By   /  May 11, 2016  /  No Comments

nosby Angela Guess

Wayne Kernochan recently shared his thoughts on NoSQL best practices in Enterprise Apps Today. His list begins, “(1) In many if not most cases, the NoSQL database should be used as a complement to an existing or additional relational database that at the least handles deeper post-arrival data analytics. (2) All else being equal, a NoSQL database that offers a broader range of ‘ACID relaxation’ — if possible, all the way from no consistency to near-ACID-compliance — is better than one that only allows no consistency. IT should plan how it will use and tune that ‘control knob’ up front. (3) If the application is aimed at Fast Data, IT should emphasize support for in-memory computing.  That typically means, among other things, implementing and using Apache Spark.”

He goes on, “I will also add a few suggestions that are less well established as part of a highly effective implementation – understandably, since the Fast Data market only began to take off less than two years ago, and thus “best practices” in that area are not fully developed: (1) ‘Data governance,’ as it is now typically called, should often be implemented at the beginning. One reason is that another hot topic with a misleading title, ‘data lakes,’ involves creating a pool of data that is not subject to the typical ETL (extract-transform-load) data cleansing of today’s analytics database architectures. Data lakes need data governance, and it is likely that some NoSQL data will move immediately into a data lake. Better to ensure NoSQL data governance compliance now, rather than create a situation in which data lake governance becomes ineffective.”

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