In-memory computing has been around for some time, and more and more businesses are starting to recognize its benefits. In-memory database systems (IMDB) rely on main memory (RAM) to store data rather than using disk storage. Traditional database systems use disk-based storage. The main advantage of using an in-memory database is performance speed. It is not necessary to perform disk read/write operations but only to read from RAM, which is super-fast.
How does an IMDB work?
Developers need to make certain decisions when adding in-memory computing technologies to their architectures. They have the option of using an in-memory data grid (IMDG) or an in-memory database (IMDB) and so it is important to understand more about how they work.
An IMDB can store relational data, key-value data, document data, and even a combination. It distributes data across multiple computers to accelerate data processing. The main advantage of an IMDB lies in its architecture as it has two layers instead of the usual three layers. This means quicker and more efficient data processing. The IMDB helps to accelerate online transaction processing (OLTP) and online analytical processing (OLAP).
Data is loaded into an IMDB in a format that’s directly usable. Data use is in the same format as the application that contains it and data access is managed by an IMDB management system.
The IMDB is designed for vertical scalability, unlike an IMDG which is designed to scale horizontally. As it is highly distributed, deploying an IMDG is easy and it can help companies to accelerate the development of applications that need low-latency.
For those that want to manage very large data amounts across hundreds of servers, an IMDG is a smart option. The high cost of RAM limited adoption of IMDGs in the past but RAM prices have dropped considerably in recent years and they have become a more affordable option.
Better performance
One of the main advantages of an IMDB is that memory is located and stored internally. A disk-based storage system means having an external element, like a hard drive. Reading data from a disk is much slower than reading data from memory.
When searching an IMDB, it takes only a fraction of the time because many of the issues that cause traditional databases to operate slowly, such as design issues and synchronization, no longer exist. According to those who use IMDBs, the difference in speed is significant. Businesses who used to take two weeks to a month to sort through billions of records find they can do it in seconds.
Scalability
A system is as fast or slow as its slowest part and in many cases, the slow part is the database. Even when a backend application is very fast, it can only serve the requests of users as fast as the database can produce data. When a system needs to serve a high volume of traffic, it makes a limit on data throughput even more evident.
At a certain point, a traditional database will not keep up with requests. It will drop requests or take a long time to reply and may even crash altogether. Adding an in-memory cache moves the breaking point much further and makes the system more flexible. Increasing or decreasing the cache cluster size enables the system to handle higher throughput and be responsive to changes in demand.
Reliability
The reliability of a traditional storage system used to be better than an IMDB and this often appealed more to businesses than quick and instant access. As RAM is volatile, data could be lost if a computer lost power. However, IMDB has steadily improved and hybrid databases now offer users the best of both worlds. They can store data on disk as a preventative measure to minimize any risk of data loss.
With the type of innovation and invention going on in top tech-based businesses, IMDBs are much more reliable than in the past. Most of them also guard against the loss of data by keeping replicas of data records in multiple computers in a cluster. This ensures data isn’t lost if a particular computer fails.
High availability
One innovation that’s been made is that IMDBs can take advantage of NVDIMMs (Non-volatile dual in-line memory modules). NVDIMMs allow a database to retain stored data even when power is lost unexpectedly due to a system crashing and shutting down.
Data can continue to run at full speed whether or not there is access to power. The IMDB will continue to read data from the in-memory cache, even when the database is offline. Downtime can be very expensive to any business so this can offer a significant advantage.
Real or near real-time decision making
In-memory data allows decision-makers to have the timely, relevant information they need. They do not have to base decisions on outdated information. This can have a positive effect in many areas of business, from customer service to marketing. With up-to-date information in hand, businesses have a competitive edge.
Cost savings
Databases are expensive to maintain and scale. To serve more requests, businesses need a larger database server or more servers and these often come at a high price. Using an IMDB means there is less need to purchase services equipped with huge hard disk drives. Resources are saved by being able to query memory over hard drives that consume power and processes.
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The cloud offers a good environment for in-memory computing. It gives businesses the opportunity to access large amounts of RAM and can help them avoid the expenses related to on-premises in-memory computing.
A final word
The benefits businesses gain from IMDBs make them a great alternative to traditional databases. They can dramatically increase performance and provide a viable option to businesses wanting to improve how they search the growing amount of data they need to handle.
Some industries that benefit from IMDBs include banking, travel, gaming and telecommunications. They are also commonly used in retail, advertising, geospatial processing, processing of streaming sensor data, fulfilling e-commerce application requirements, and more. Leveraging an IMDB that can quickly deliver data enables users to spend more time analyzing and making decisions.
