Databases
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    <p>Relational databases provide solid, mature services according to the <a href="http://en.wikipedia.org/wiki/ACID" rel="noreferrer">ACID</a> properties. We get transaction-handling, efficient logging to enable recovery etc. These are core services of the relational dbs, and the ones that they are good at. They are hard to customize, and might be considered as a bottleneck, especially if in you don't need them in a given application (eg. serving website content with low importance; in this case for example, the widely used MySQL does not provide transaction handling with the default storage engine, and therefore does not satisfy ACID). Lots of "big data" problems don't require these strict constrains, for example web analytics, web search or processing moving object trajectories, as they already include uncertainty by nature.</p> <p>When reaching the limits of a given computer (memory, CPU, disk: the data is too big, or data processing is too complex and costly), distributing the service is a good idea. Lots of relational and NoSQL databases offer distributed storage. In this case however, ACID turns out to be difficult to satisfy: the <a href="http://en.wikipedia.org/wiki/CAP_theorem" rel="noreferrer">CAP theorem</a> states somewhat similar, that availability, consistency and partition tolerance can not be achieved at the same time. If we give up ACID (satisfying BASE for example), scalability might be increased. See <a href="http://blog.nahurst.com/visual-guide-to-nosql-systems" rel="noreferrer">this</a> post eg. for categorization of storage methods according to CAP. </p> <p>An other bottleneck might be the flexible and clever typed relational model itself with SQL operations: in lots of cases a simpler model with simpler operations would be sufficient and more efficient (like untyped key-value stores). The common row-wise physical storage model might also be limiting: for example it isn't optimal for data compression.</p> <p>There are however fast and scalable ACID compliant relational databases, including new ones like <a href="http://en.wikipedia.org/wiki/VoltDB" rel="noreferrer">VoltDB</a>, as the technology of relational databases is mature, well-researched and widespread. We just have to select an appropriate solution for the given problem.</p>
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    1. POWhy are relational databases having scalability issues?
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    1. CO"These cannot be turned off". That is a blatant lie. DB2 allows to turn journaling (logging) off (and I 'd be surprised if any of the other big dogs lacked the equivalent in their products). And guess what, if you do that your update programs may get to run as much as twice as fast. Of course the price you pay is taking backups before such an update run, and the time it takes to restore if the program fails. Of course this typically isn't done, but to say that it "**cannot**" be done merely displays ignorance rather than knowledge.
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    2. COYes, "cannot" might be too strong here. I don't know all DBs; however, for example use of Oracle nologging clause only reduces log size, but does not turn it off. Transaction handling and writing undo information definitively cannot be turned off, or, if turned off, the DB is not ACID compliant any more. Am I wrong? And one more bottleneck: the data model and SQL. Flexible model with clever algorithms; in lots of cases a simpler model with simpler operations would be sufficient and more efficient (like untyped key-value stores).
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