How Have Databases Changed in the Past Two Years?

Since the early days of computerization, data storage systems have always been a critical part of any information technology infrastructure. New database development solutions and computing applications, such as artificial intelligence, deep learning, and blockchain, have significantly increased the performance requirements of data processing systems.  In this brief review, we decided to understand how databases and the approaches to information storage have changed over the past two years.

2017: SSD Popularity Is Growing

According to IDC, in 2017 we were able to observe the 76% growth of the all-flash market in the corporate sector value. Companies engaged in this area were able to earn $1.4 billion. At the same time, sales of hybrid flash arrays reached $2 billion. Despite the popularity of SSD, hard drives did not plan to leave the market completely. HDD manufacturers made an attempt to increase performance by increasing disk capacity.

2018: Data Goes to the Cloud

Since 2018, cloud storage has become one of the main trends. It became possible to choose the database cloud service from a variety of options. For example, Snowflake began offering new features in managing their data warehouses, while large database cloud service providers, such as Azure and Google Cloud, benefited from popular products such as MySQL and Postgres, offering them as a managed service.

2019: AI and ML Are Now Inseparable

Modern databases are already working in conjunction with artificial intelligence and machine learning. So, most recently, Huawei launched the AI-Native GaussDB type database, as well as the distributed data warehouse FusionStorage 8.0 with high-performance indicators.

According to Huawei, the GaussDB database combines two major achievements. First, of all modern database development solutions, only GaussDB has AI functionality built into the full life cycle of distributed databases. This will allow them to self-setting, self-test, self-repair, and self-service.

Right Now: Explosive Data Growth

Now we can see the process of advanced data development, as people generate an increasing amount of data. If we consider that this data is then copied to the processing centers and in the cloud, this only increases the amount of memory needed to store it. To date, the number of data generated by the machines is relatively small.

However, the situation will change by the end of 2019, as solutions and technologies such as autonomous cars, intelligent factories, Internet of Things (IoT) and home automation will generate additional data streams that need to be stored. Their expected volume is so large that the current data storage and advanced data development philosophy will require a serious revision very soon.

 

 

 

 

 

 

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