The trade-offs involved in using abstracted data in relational databases versus non-abstracted data in non-relational databases, relying on pre-abstraction versus self-abstraction of high-volume data streams, and so on are not obvious, will change as technology involves, and will depend on the company and the problem.

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For example, most organizations have their data in structured relational databases like Oracle, but much of the data generated today is unstructured, high-volume web data or machine data.

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Why on earth in this day of deep relational databases and high-speed international computer networks do we need printed passports?

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There were limitations in what could be analyzed, due to the inflexibility of data warehouses and relational databases, but the process for cleansing, sorting and analyzing data was well understood as a complete cycle.

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In a few years, will we be looking at hybrid databases that take advantage of both relational and non-relational models?

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What the hardware is that goes underneath Oracle (or Ingres etc, the other relational databases, if any of them still exist so long ago was my involvement in this world) is very much a secondary consideration.

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In 1977 Larry Ellison, Bob Miner and Ed Oates founded Software Development Laboratories around a new IBM technology called relational databases.

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The vast majority of this growth is occurring in the realm of unstructured data, i.e. data that does not fit well into relational tables such as databases.

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