Big Data vs Important Data

Big Data is everywhere. Big Data is being talked about, collected, processed. Huge efforts are made to make sense out of Big Data. Big Data is about money - if you can come to some conclusions analysing big data, you can save or earn money - that is what the big data is about. The humankind floods the storage servers with its waterfall of data, most often not very important from the original source point of view, mostly meaningless from a single entity point of view, but meaningful (hopefully!) en masse.

Big data promises the Holy Grail in FinTech institutions, with risk assessment, decision making, fraud detection and many other domains, hidden usually from non-regulatory eyes. Why are big data systems so popular? They promise to run on commodity hardware, for a fraction of price tag that would be attached to proprietary, legacy solutions, big data or not. They promise massive horizontal scalability, handling burst workloads and much more. Of course, when you look at more complex scenarios, you'll find out that the clusters are built with top-shelf dedicated server hardware, that licencing is not that cheap at all, and that the scalabilty has to be precisely designed and baked into the application - otherwise you won't go anywhere.

Big Data vs RDBMS

The market for the NoSQL, big data solutions has grown tremendously in the recent years, but the fragmentation begins to take its toll. There are first signs that the NoSQL vendors are folding, being taken over by bigger enterprises, or completely disappear from the market. This is good - the fragmentation of the market has been confusing for the customers, who have difficulty with choosing the right solution. And often the solutions prove to be rather less sparkling than advertised and require a lot of hand holding, 24x7 support, unplanned releases, patches etc.

Let the strongest survive.

In the meanwhile, the RDBMS market is strong, very strong. The companies who have not-so-big data are not going to invest millions and millions of dollars to replace their legacy systems with big data solutions, with all the fancy document oriented, key value pairs or hybrid systems which require complete rewrites of their applications. The RDBMS systems hold, you know, the boring kind of data. Transactions, inventories, orders, balances, accounts and the likes. The systems offer one, very important feature for these data - transactional processing. 

The transactions are logged write-first to the permanent storage, the old way, invented in seventies or earlier. Owners of these systems know that their databases can be restored to a point of time in case it is required - if their DBAs did not screw up. 

 This is the Important Data.

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