In-memory database computing is a fast-growing market segment that uses a highly developed architecture that enables data to be stored inside computer memory instead of disks.
The greatest setback experienced with disk-based databases is their bottleneck input and output that kills big data performance. To solve this challenge, businesses adopt systems that allow distributed caching but this method is also limited. This is where the in-memory database comes in.
In-memory database
The creation of an in memory data grid has helped solve a big data challenge experienced by every business a few years back. Before its creation, RAM was still available as working memory as long as the system was on. Just like today, it contained all operational programs and all data that was important to help the programs run.
The only challenge that prevailed was that once the computer went off, all data in RAM went off too and could not be available the next time the computer was on. This was regardless of whether the system was switched off deliberately or it was due to lack of power or system error.
An in-memory database becomes the solution for the loss of data problem. The system uses the same strategy of storing data in the working memory where all the programs are running from.
However, an in-memory database is boosted by improved software that enables it to keep data even after the computer shuts down. The data is not lost and immediately the system is switched back, all the data that was in the working memory is available for access.
IMDB functionality is made possible by a database management system which is what moves and stores data in the RAM. As a result, businesses access their data fast, anytime it’s needed.
How in-memory database stores big data
The main goal of developing any type of technology is for helping sales grow in any business environment. The in-memory database is not designed as a sales promotion tool but as a storage store where data can be accessed and used to help businesses make informed decisions on how to improve their sales, products, and service to customers.
To help it store big data, an in-memory database uses several sets of technologies. Before it stores data in RAM, its infrastructure helps it distinguish data and store it in rows and columns. When arranging it into rows, all consolidated data at any one time is stored in one row. For example, the system may collect data that has unique values like town, state, country. In row-oriented storage, it will be arranged in a row like – town 1, state 1, country 1, town 2, state 2, country 2.
The same data, when stored in a column-oriented style, would be arranged thus – town 1, town 2, state 1, state 2, country 1, country 2 in a format known as columnar. This method of data storage helps minimize the volume of available data at any given time. Consequently, the system can accommodate more data and greatly reduce transmission times.
Properties of in-memory database
A strong in-memory database has several properties that help businesses get high-end benefits.
An in-memory database is durable: All transactional data assigned to the database is stored until the transaction process is complete. If there is an error or power loss that makes the system shut down, the data will still be available once the system is back and the transaction will not be lost.
Atomicity: IMDB system does not allow multiple transfers of data in streamlined processing. It only allows a single transfer at a time and thus keeps each file unchanged even in a situation where part of the entire transaction fails.
Isolation: every transaction carried out inside the in-memory database is independent. It gets isolated from all other transactions even if they are activated concurrently.
Transaction consistency: All data running in an in-memory database strictly follow the set rules and this makes sure it’s consistent all through.
Technologies used by the in-memory database
The architecture of an in-memory database uses various technologies to make it effective and beneficial to any business. The main technology it uses is a data warehouse which enables it to collect, compress, and store data for both short-term and long-term use.
To help increase RAMs capacity to the level of Terabytes, the IMDB uses 64-bit technology. For better performance of data processing, the system uses multi-core processing technology.
Steps during the working of in-memory database
The IMDB system enables data to be available and updated all the time in RAM without having to move it from the hard disk through the following process. Immediately when the system is on, IMDB loads all data available on the hard disk into RAM. This eliminates the need to load data while the system is running.
Anytime there is a data update, IMDB readjusts and updates it in the RAM. All current transactions are stored in transaction logs to allow correction of errors in a roll-forward process. All data is processed strictly following the ACID rule. Constantly, the system replicates data and backs it up in the backup servers.
Advantages of using an in-memory database
The main benefit of using an in-memory database in a business environment is the kind of speed achieved. The system can process data at a very high speed, thus taking less time to complete any single transaction.
The system streamlines the processes by avoiding multiple data transfers and thereby reducing the amount of RAM needed to store data. It removes duplicated data and makes the entire process simple by minimizing activities inside the CPU.
Compared to disk-optimized databases, IMDB minimizes the number of commands sent to the CPU to make response time fast. It compresses data before loading it into the random access memory. This helps lessen the time taken to retrieve data from disks and move it into RAM. As a result, the entire process becomes streamlined and easily accessed.
It is possible to move big data
Using big data management technology, an in-memory database has made it possible to access, store, and process big data fast in both the systems that have storage disks and those without. Queries are processed fast and thus, operational cost is reduced. Compared to traditional methods, an in-memory database enables big data movement and updates in real-time.
