MSFTCOST04-BP03 Consider purpose-built databases
Purpose-built databases are gaining traction among businesses adopting modern architectures like microservices, as they can precisely accommodate specific data access patterns. These databases, whether SQL or NoSQL, offer application teams benefits like reduced costs, enhanced scalability, and improved resilience. By selecting the right database for each specific use case, teams can optimize their data management while leveraging cloud advantages for more efficient solutions.
Desired outcome: By adopting purpose-built databases tailored to specific workload requirements, application teams will optimize data management, reduce costs, and enhance scalability and resilience. This approach will lead to more efficient cloud-based solutions, whether using SQL or NoSQL databases, and minimize undifferentiated heavy lifting in database operations.
Common anti-patterns:
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Using a single database technology for all applications and workloads, regardless of their specific data access patterns or requirements. This can lead to suboptimal performance, scalability issues, and increased costs.
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Adopting multiple specialized databases for every minor variation in data needs, resulting in a fragmented and overly complex data architecture that increases management overhead and potentially negates cost savings.
Benefits of establishing this best practice:
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Purpose-built databases are designed to handle specific data access patterns, resulting in improved query performance and overall system efficiency tailored to each application's unique needs.
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By choosing databases that align closely with workload requirements, organizations can avoid over-provisioning resources and reduce unnecessary licensing costs associated with general-purpose database solutions.
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Purpose-built databases often come with built-in features for horizontal scaling and high availability, making it easier for applications to handle growth in data volume and user traffic while maintaining robust performance and reliability.
Level of risk exposed if this best practice is not established: Medium
Implementation guidance
Begin by analyzing your application's data access patterns, query requirements, and scalability needs. Identify distinct workload characteristics across your application portfolio and map them to appropriate purpose-built database solutions. For new applications, design the data architecture with these specific requirements in mind from the start. For existing applications, consider a phased migration approach, starting with the components that would benefit most from purpose-built databases. Evaluate AWS purpose-built database options such as Amazon DynamoDB for high-performance NoSQL needs, Amazon RDS for traditional relational workloads, or Amazon Redshift for data warehousing, ensuring each choice aligns with both technical requirements and cost optimization goals.
Implementation steps
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Analyze current data access patterns and requirements across your application portfolio
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Identify suitable purpose-built database solutions for each distinct workload
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Develop a migration strategy, prioritizing components that will benefit most from the change
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Implement and test the new database solutions in a staging environment
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Gradually migrate production workloads, monitoring performance and costs throughout the process
Resources
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