In-memory databases are differentiated from other database management systems by the way they store data. Instead of using a disk storage mechanism, an in-memory database relies on main memory for computer data storage. For non-technologists, this might seem like a purely semantic distinction, but relying on memory for data storage actually offers several powerful advantages.
First and most importantly, in-memory databases are faster than traditional database management systems. A key reason for this is because memory access is much faster than having to access disk storage. All data is stored and managed exclusively in main memory. The speed upgrade should make intuitive sense: you are essentially eliminating an entire step in accessing data. Another key reason for this boost in speed is the fact that internal optimization algorithms for in-memory databases are less complex and require fewer CPU instructions to get the right data at the right time.
Secondly, in-memory databases are more efficient than traditional database management systems because there is less “seek time” when querying data. This, too, should make intuitive sense: when looking up data, it’s a lot easier to find what you need when the data is stored right there in main memory. This is known as minimal request time, and is absolutely essential for any industry where real-time performance is crucial.
That being said, in-memory databases are not a perfect solution. Until recently, for example, there were questions about what happens to data stored in RAM in the event of a power loss or similar event. But that drawback has largely been addressed by a number of workarounds, such as the creation of non-volatile RAM technology that can continue to run, even in the event of a power failure.
Recently, so much attention has been focused on in-memory databases because they are a much better fit for any real-world application that requires microsecond response times, as well as any application that must deal with extremely large spikes in traffic at any time. In the mid-2000’s, for example, in-memory databases became popular as a way of offering real-time analytics to large corporate customers. As the price of RAM continues to fall, and as new, more powerful multi-core processors hit the market, it’s easy to see why this trend will continue.
Thus, as can be seen, in-memory databases are superior in terms of speed, efficiency and reliability. For any application where response times are measured in microseconds, they offer an obvious value proposition. Just a decade ago, it might have been possible to use disk storage mechanisms, but the creation of a truly real-time digital landscape has also created the obvious need for in-memory databases.
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