The main reasons in-memory databases have not been popular in the past are high costs and the lack of durability. RAM has historically been expensive, and IMDB stores all data in RAM, so a power outage or RAM crash can cause data loss. These two factors may have affected the evolution of in-memory databases but this has changed over time. In-memory databases have become more affordable as the cost of RAM drops and there are ways to prevent loss of data.
What is a high-performance in-memory database?
The need for speed in today’s business world is pervasive and traditional disk-based databases don’t offer it. Customers increasingly expect companies to meet their needs instantly, offer real-time visibility, and personalize interactions. It is no surprise that high-performance in-memory databases are in demand. The computer's main memory is the primary location for storing and accessing data, rather than the disk drive. Accessing the data stored in memory eliminates the time required to query data from a disk.
High-performance IMDBs have highly scalable architecture, a flexible data structure and offer low latency and high performance. They allow business owners to get real-time insights and make decisions before data becomes redundant.
A modern IMBD not only stores data in memory but also performs operations within memory. It allows all types of data to be stored in a single system, including structured transactions and unstructured ones like video and emails, all with the same fast access capabilities.
The distributed data infrastructure means a cluster of computers work in parallel to offer quicker processing, more storage and better transfer speed of unstructured data. The data is in a directly usable format without any barrier of encryption or compression. It is possible to navigate from index to row or column.
What is an in-memory data grid? It is different from an in-memory database (IMDB), although it also stores information for instant access. It makes intensive data processing applications quicker and offers scalability without significantly changing an existing database.
Advantages of a high-performance in-memory database
High speed: Users don’t have to access slower secondary storage when they want to query or update data. They can access data directly from where it is stored in the main memory. They do not have to perform disk read or write operations to return data and reading from RAM is blazingly fast. Fast performance is, therefore, one of the major benefits of high-performance in-memory databases which can perform millions of read/write operations per second, each taking less than a millisecond.
Low latency: A backend application may be lightning fast but it only serves a user’s request as fast as a database can produce data. This is even more evident when a system has to serve high traffic volumes. These may overwhelm a database so it starts dropping requests or taking a very long time to reply. The whole system may even become inoperable. Low latency is possible when using a high-performance IMDB as minimal time is taken from when a user takes action and an application responds.
Improved reliability: With a high-performance in-memory database, it is possible to serve more requests and do so in a safer way. Any spikes in traffic are unlikely to bring the system down. Less downtime means less loss of revenue as downtime is expensive.
Easy scalability: The distributed data infrastructure offers easy scalability and adding additional RAM can increase performance with relative ease. It makes switching between different applications easy and allows multiple applications to be open without making the whole system sluggish.
ACID transactions are supported: In-memory databases support ACID transactions (atomic, consistent, isolated, durable), although durability can be challenging. There are now a number of ways to support durability.
Persistence in modern IMDBs allows them to run at full speed and still maintain data in the event of a power failure. Non-volatile random access memory (NVRAM) is a way for in-memory databases to maintain data when the electricity goes out. Having a decent number of database replicas and not having them all on the same electrical grid means in-memory databases can be nearly as reliable as traditional databases.
Main use cases of high-performance in-memory databases
High-performance in-memory databases are used mostly for real-time applications that require high-performance technology. Finance, telecom, intelligence and defense industries all benefit from using them. For example, good payment gateways have to function 24/7 and do the job with no delays. Even one minute of downtime causes a problem. Any applications that require real-time data access need to use them, such as travel apps, reservation apps, streaming apps and call center apps.
In-memory databases support transaction processing where demand can be random and there may be unpredictable spikes in incoming traffic. They are also very good for companies where data is expanding rapidly, such as medical device monitoring, online banking and credit card sales, e-commerce sites, interactive gaming, and streaming sensor data (Internet of Things).
The Cloud and an In-Memory Database
The cloud provides organizations with the opportunity to get more out of in-memory computing. They can access large amounts of RAM and avoid the expense of on-premises in-memory computers. Storage is also more reliable, thanks to using virtual machines with automatic failover and redundant hosts. This means data disruption does not result in data loss. These protective measures are more difficult to develop in an on-premises computer system.
Cloud service providers now offer managed solutions for in-memory databases that take the heavy lifting off the shoulders of businesses when it comes to capacity management, failover, backups and much more. This makes high-performance in-memory databases much more attractive and accessible.
Conclusion
As data continues to explode, high-performance in-memory databases are in demand. A high-performance in-memory database provides an important foundation for digital transformation because digital enterprises can’t use stale data to make real-time decisions. Now that in-memory pricing is lower and memory capacity keeps expanding, enterprises need a high-performance in-memory database to drive real-time insights and thrive in today’s economy.
