The space in random access memory used as temporary storage is what is called cache. It is found between the apps and databases to provide high-speed access to recently requested data. It reduces the time taken to process a task that must be retrieved from storage before it’s processed.
On the other hand, an in-memory database provides storage in RAM, eliminating the need to rely on traditional disks. All data processed in RAM responds quickly, thus saving time. Data stored in RAM is ready for use and available anytime it’s needed.
How in-memory cache and in-memory database works
For the in-memory cache to work, it sets aside some part of the RAM that will work as the cache. Before an application reads data from storage, it first checks to see if the data is available in the cache. If it finds it, it reads it from the cache but if it doesn’t, it reads it from the source. Once the data is retrieved from the source, it is written on the cache so that it’s available next time it’s retrieved. This process of using in memory cache makes sure the recently accessed data is available for fast retrieval, thus eliminating the long process taken to read data from storage.
In-memory database, on the other hand, makes data available all the time it’s needed. It is also called the main memory database because it’s found in the main memory. Because the data is not located in a hard disk, it eliminates the need for I/O tasks before accessing and processing data. The process reduces the time taken to retrieve or store data.
The structure of cache memory and in-memory database
Cache memory provides quicker data access from the random-access memory. Due to its location, the CPU can access it at a greater speed compared to the main memory. The cache is located between the main memory and the CPU to help move data between the main memory and processor at high speed.
From the cache to the CPU, data is moved as word transfer but between the main memory and the cache, it is transferred as blocks, also known as pages. Speed is of the essence on both ends and the in-memory cache provides the needed speed. There is another level called the multilevel cache. This type of cache structure is used by businesses that have large sizes of often accessed data. When the data size grows too much, it might affect cache processing speed.
Businesses, in this case, organize different caches at multiple levels to help improve speed. Because smaller caches have greater speeds, they are placed closest to the CPU while the larger caches are placed further from it. The overall goal is to help cache perform better at a higher speed.
Data found in the in-memory database is always fresh because it is updated constantly. Instead of looking for the data in disks, in-memory databases make it available in real-time. It is expensive to move data but when it is stored in the main memory, it becomes a lot easier and cheaper to move or manipulate it. It provides a better way to carry out more tasks from the main memory, such as machine learning models.
In-memory cache and in-memory database use cases
When businesses are looking for tailored cloud solutions, both the cache and in-memory databases become important. A major use case for the in-memory cache is to increase the speed of database apps, especially those that are accessed more often. It shortens the time required to read from the database, thus reducing latency due to frequent access to the database. This use case is more common in businesses that have a higher demand for high-volume data processing.
In memory, the cache is also used in situations where queries require to be processed fast. Those are queries that involve complex processes that are done frequently. An example would be a query involving business intelligence infrastructure that is accessed frequently by multiple users. Cache provides a quicker response in such scenarios. In memory, databases are used in situations that require high data security integration. It helps detect anomalies in data in real-time and thus helps prevent fraudulent data before it overworks the system. Customer service personnel use in-memory databases to perform real-time data analytics that help them respond to customer needs fast and thus increase satisfaction.
Businesses that use prepaid calling services can track their credit balances thanks to the simplicity of solutions provided by in-memory databases. Fleet service providers take advantage of in-memory databases to analyze data from the cloud to help them make intelligent decisions in routing road traffic.
In-memory cache and in-memory database advantages
Compared to the main memory, data found in the cache memory is many times faster. The time taken to process data on cache memory is far much less than the time it would take to process the same data from other storage solutions. In an in-memory cache scenario, the CPU finishes tasks faster due to an increase in data access speed. The CPU not only works faster but also performs better. Data outputs are faster because recently accessed data is stored in the cache.
The main advantage of using an in-memory database is speed. When speed is achieved, a business can reap many other advantages. One of the benefits is giving businesses real-time value because of low latency in data processing. As a result, businesses can use available data to make intelligent business decisions within a very short time. They can take advantage of the data before losing its value and thus gain capital value at the earliest opportunity.
In memory, databases provide predictable data scalability because it is available in the main memory. The business can scale any piece of data without losing latency. The data is also highly available, which helps eliminate downtime that might lead to loss of revenue. The gaming industry benefits a lot from in-memory databases. When publishing data in their game leaderboards, the industry needs to leverage data in real-time. Due to the fast availability of data in the main memory, the industry can publish the results of live games.