The 2020 Database Developer Roadmap

The transforming business model of lending software instead of selling them has increased its adoption on a much broader scale. The software lending business model has made available the large components available to software developers and they can use it to build more complex systems hence we are delivering software at a much faster pace.

Process improvements have always been an integral part of organizations and that’s why the software development industry thrives as it contributes a lot in improving processes and automating tasks.

The easy availability of diversified software, artificial intelligence, and lower cost to run automated digital and physical infrastructure has led the movement of industry 4.0 which surged the demand of web developers in the industry.

Database developer’s roadmap 2020

The gap between what’s taught in schools, colleges and what’s demanded in the software industry has led us to write this article “Database developers roadmap for 2020” in conjunction to our upcoming article “web developers roadmap for 2020”

Learn Database development

We have been using databases for more than three decades and they have been working pretty well. Since we have started moving towards web applications and cloud infrastructure to reduce the cost and latency, we started facing many problems with our conventional relational databases.

Read: “8 Cool Web Design Trends in 2020

Relational Databases

Relational databases were used to store data where the aggregation point (i.e. reference point) to compute and fetch data can change a lot such as in banking transactions, although the processing of these transactions took more time they were preferred in this use case.

Relational databases need to be ACID compliant to maintain the integrity of data for highly important transactions. To stay ACID compliant, we often have to lock transaction to some records that are under processing and use centralized data.

The problem web developers face in the cloud era was that centralized databases were increasing latency as the end-user could be sitting thousands of miles away from the server where the application is running, this latency could only be reduced if we create distributed clusters of these databases. Using the clustered approach creates another problem i.e. violating the ACID compliance, hence the whole solution needed to be implemented in a new way.