4 Reasons To Turn To In-Memory Solutions

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#1

The need for performance is an all-time high. Many players in the market need fast data processing to ensure optimal system performance and growth. Many applications require instant results including weather reporting, intelligence, live streaming or real-time apps.

In today’s article, we will be focusing on in-memory solutions. In-memory solutions provide better performance and scalability. But, are they even worth it? We will be discussing four reasons why businesses and enterprises should turn to in-memory solutions. Let’s gets started.

1. They are fast

The number one reason to move to the in-memory solution is for the speed they offer. The in-memory solution provides the best speed possible in terms of sequential and random access. They are lightning fast when it comes to storing, accessing and computing information. The random access can be done as low as tens of nanoseconds(1e-8 seconds). Read and write speeds are also fast, and can reach 1 GB per second or even higher. All of these happen by maintaining the basic characteristics of a database which include Atomicity, Consistency, Isolation and Durability. In-memory solutions use in-memory database management system (IMDBMS).

2. Real-time business decisions

By using in-memory solutions, any business can now make real-time business decisions. It provides them with the self-service analysis capability which in turn make them agile in their decision making. The team working behind critical processes can now use sophisticated in-memory solutions such as Gigaspaces to ask for queries, do modelling and prepare data that matters the most. Once done, they are now ready to make decisions that matter to their business.

3. Scalability

In-memory solutions can help businesses scale and solve their problems using the help of databases such as Hadoop and other scalable database solutions. Enterprises do want to move ahead of Big Data and enter a playing field where they can do things faster and scale as they want. Platforms such as SAP HANA are a prime example of providing scalability using in-memory solution. By hosting the whole database in-memory, there is visible performance improvement which offers real-time benefits. Also, in-memory solutions work with traditional storage by generating snapshots of the data in the memory, giving it the consistency, it requires to work efficiently.

4. Reduced IT costs

In-memory solutions also impact the cost of the whole infrastructure setup. It reduces it a lot, and it does it by removing the need for storing pre-aggregated data or data indexing in OLAP aggregate tables or cubes. By doing so, the whole cost of the IT setup is reduced and enable faster implementation of their business processes including BI/BA applications.

Final thoughts

In-Memory solutions are here to stay. Enterprises need to realize that there are alternative solutions to Big Data regarding performance and scalability. Arthur Code also discusses the same fact in his article on how in-memory solutions are confronting the big data challenge.

With advancement in technology, there is no denying that new technology and solutions will always offer a better approach. However, in-memory solutions might have limitations related to some systems or business process when integrated. That’s why we recommend businesses to thoroughly study both advantages and disadvantages before implementing or using in-memory solutions.

So, what do you think about the in-memory solution? Are they capable of changing the industrial landscape? Comment below and let us know.