As digital revenue moves to the cloud, there has been significant growth in database management systems. According to research firm Gartner, the database management systems market has seen six years of consecutive growth.1 Worth $38.6 billion in 2017, it has doubled over the past five years to hit almost $80 billion in revenue last year.
This will be critical, as databases play a principal role in business environments today, amidst growing data volumes and demand for data to drive richer customer engagement. Gartner also notes that managed cloud database systems now account for more than 49% of the market’s overall revenue.
The increasing reliance on databases underscores the need for these systems to be scalable and to be able to scale quickly. Often, this means legacy environments running Microsoft SQL Server are no longer cost or operationally efficient.
The need for scalability, flexibility and performance has driven the move to the cloud, as organizations look to gain business benefits of cloud-native technologies. Gartner predicts that by 2022, 75% of databases will be deployed to the cloud.2
Along with the move to the cloud, open source systems are emerging as cost-viable alternatives to Microsoft SQL servers. Enterprise-grade open source database engines, such as PostgreSQL, have fuelled greater accessibility to relational databases that once were deemed expensive, luxury systems.
Before making the transition, companies first must establish a database strategy that is right for their business requirements. They need to assess, amongst other things, how much CPU and RAM resources are required and how much are idle. This will help avoid sudden surges in cloud-associated costs and mitigate the impact on their business.
Substantial instances are typically required for on-premises databases, and it can cost more to maintain the same volume on a cloud platform. Doing so will not be necessary in the cloud, since database resources can scale easily and quickly based on demand.
Hence, companies need to determine what they actually require in a cloud environment, rather than simply retaining the same database structure they ran on premises. Such right-sizing exercises are essential and should be completed before the migration starts.
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Organizations would be wrong to assume they can do so without the right tools and the necessary expertise and skillsets to drive the migration.
For one, companies will need to determine whether their application architecture running on Microsoft SQL Server can support open source systems. They also must assess compatibility issues and decide if a new database with new functionalities should be created.
Schemas may need to be converted and application codes rewritten to interact with the database. These will all have to be tested before they are pushed to production for the migration.
To help companies work through the complexities, cloud vendors such as Amazon Web Services (AWS) offer a range of tools that automate and streamline crucial processes. For example, Babelfish for Aurora PostgreSQL enables Amazon Aurora to understand commands from applications written for Microsoft SQL Server.
While you can automate the migration of your Microsoft SQL Server schema and data using the AWS Database Migration Service (DMS), application refactoring and other work is required to migrate the workloads.
With Babelfish, Aurora PostgreSQL understands Microsoft’s proprietary SQL dialect for SQL Server and supports the same communications protocol, so applications originally written for Microsoft SQL Server can work with Aurora with fewer code changes. This reduces the effort needed to modify and move applications running on Microsoft SQL Server 2005 or newer to Aurora. It provides faster and more cost-efficient migrations that also come with lower risks.
You also can perform a quick compatibility assessment of your Microsoft SQL Server databases with the help of Babelfish Compass and determine how complex the modernization path to PostgreSQL will be. Since tools such as Babelfish are open source and available via GitHub, under Apache 2.0 licences, users will not be locked into any software vendor.
Because it is a built-in capability of Amazon Aurora, Babelfish does not have an additional cost and can be enabled on Amazon Aurora in the Amazon Relational Database Service (RDS) management console.
Enterprises can get further help from Amazon partners such as Rackspace Technology, which offers a discovery-based database migration and modernization program for AWS.
Rackspace Technology specialists will establish the return on investment of a database migration or modernization exercise and determine the combination of cloud technologies and architectural designs that offer the lowest total cost of ownership.
The fully funded four-week customer engagement exercise aims to reduce database licensing costs and vendor lock-in by leveraging AWS database technologies, such as RDS PostgreSQL, RDS MySQL and Amazon Aurora.
Rackspace Technology will help customers tap AWS solutions to reduce their database management and support microservices architectures.
Its database migration and modernization program for AWS further encompasses a review of the customer’s current database technology, application assessment, impact assessment of application migration and evaluation of current database licensing and costs.
Armed with more than 2,500 AWS accreditations, Rackspace Technology will work to develop a detailed migration plan that ensures customers have a database modernization roadmap that is just right for their organization.
1 “DBMS Market Transformation 2021: The Big Picture,” Gartner, April 16, 2022
2 “Gartner Says the Future of the Database Market Is the Cloud,” Gartner, July 1, 2019
