Overview
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Get a holistic overview of the essential elements of designing and implementing highly scalable and available relational databases.
Syllabus
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Introduction
- Challenges to scaling relational databases
- What you should know
- Business requirements for database scalability
- Identify use cases for data
- Identify security and compliance requirements
- Estimate data growth
- Challenge: Identify business requirements in a scenario
- Solution: Identify business requirements in a scenario
- Choose a datastore: SQL, NoSQL, or analytical?
- Identify schemas
- Identify key entities
- High-level physical design
- Challenge: Revised database architecture
- Solution: Revised database architecture
- Human-scale and machine-scale data
- Different data ingestion strategies
- Designing scalable user interfaces
- Message queues to buffer ingested data
- Data modeling for scale: Event sourcing
- Distributing workload: Command Query Response Separation (CQSR)
- Challenge: Services and APIs for a scable user interface
- Solution: Services and APIs for a scable user interface
- Transactional vs. analytical queries
- Indexing for transactional queries
- Materialized views for transactional queries
- Using read replicas to improve query performance
- Understanding write-ahead logging
- Denormalizing for analytical queries
- Aggregation and sampling for analytical queries
- Challenge: Optimize a data model for an analytical queries
- Solution: Optimize a data model for an analytical queries
- Monitoring relational databases
- Reducing latency with caching
- Partitioning for scalability
- High-availability architectures
- Data lifecycle management
- Challenge: Understanding database DevOps
- Solution: Understanding database DevOps
