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java,nosql,bigdata,theory,big data

In-Memory Data Grids Put NoSQL to Shame When You Look at the Majority of Customers

We had this discussion in the office another day and I couldn’t figure out why popular NoSQL products like MongoDB, CouchDB, Cassandra, etc. are generally years behind on some of the core scalability and performance technologies behind established In-Memory Data Grid vendors like Coherence, GridGain, GigaSpaces, GemFire?

It’s not a feature by feature comparison that I’m talking about – all of these products have plenty of unique features. It’s just the fact that while IMDG were scaling to 100s and 1000s of nodes and working in mission critical systems for years now – NoSQL products are simply not there and moving there rather slowly (if at all).

I can’t remember ever having an IMDG product with a global-lock based implementation (like MongoDB “engineered”), as an illustration to what I’m talking about it.

Then it dawned on me while here at HPC for the Wall Street conference (where not a single NoSQL vendor was present, btw): it’s customers…

Look, 90% of NoSQL usage comes from the same crowd as a typical memcached users: non-critical, “moms-n-pops” websites. 90% of IMDG/IMCG usage comes from mission critical systems.

Different customers => different requirements => different products…

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