Enterprise big data workloads are incredibly diverse and require a smart mix specialized and commodity hardware and software.
Factors including the speed with which data is piling up and the rate at which the cost of conventional databases is escalating are pushing people who should know better to consider using NoSQL in situations where it's wholly inappropriate. That category includes stores of core customer and product data and related transactions that have to exist in a single source of truth and use standard access techniques.
Now, we get why IT is intrigued. Just 11% of the 760 respondents to our InformationWeek 2012 State of Database Technology Survey are very satisfied with licensing costs and terms for their conventional databases. And the broad "NoSQL" label does indeed reflect the main attraction: Often, these systems are open source or quite inexpensive and can run on commodity hardware.
But remember, there's a reason structured data and relational database management systems have ruled the enterprise roost since the '80s. SQL--along with technologies like distributed caching platforms that have helped cement its dominance by bringing in-memory caching and clustering of data--is the go-to choice for mission-critical, high-performance use cases such as airline reservation systems and financial/securities applications. And the fact is, those jobs aren't going anywhere--especially to NoSQL options like MongoDB on a white-box server--no matter how much the hype machine might suggest otherwise.
However, IBM, Oracle, and Microsoft are seeing an unprecedented challenge to their SQL licensing money machines thanks to enterprise data workloads that are getting more diverse, larger, and more complex. In those cases, IT will trade stringent data consistency for low latency and a favorable cost versus performance balance. This is where NoSQL technologies like those outlined in the chart below ...