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ATAM Database Concepts

Cross-cutting Concerns

  • Performance and Scalability: We will discuss how each type scales and performs under different workloads.
  • Data Integrity and Consistency: We will contrast the approaches to data integrity and consistency, especially compared to ACID properties in RDBMS.
  • Maintenance and Operational Complexity: We will evaluate the maintenance needs and operational complexity of each type.
  • Security: We cover security features and concerns relevant to each database type. We put a focus on scalable RBAC systems.
  • Community and Ecosystem: We will also assess the community support, availability of tools, and integration capabilities.
  • Cost Considerations: Next, we discuss cost implications, including open-source versus proprietary solutions and cloud-hosted versus on-premise.
  • Trends and Future Directions: Finally, we iscuss emerging trends in database technologies and potential future developments.

Distributed Database Concerns

Covering core architectural concepts in distributed databases is essential for understanding their capabilities, challenges, and best use cases. Here are some key concepts you should consider including in your book:

Distributed Transactions

  • ACID Properties in Distributed Context: Explain how Atomicity, Consistency, Isolation, and Durability are maintained across multiple nodes.
  • Two-Phase Commit (2PC): Discuss the two-phase commit protocol as a method of ensuring all-or-nothing transaction execution across distributed systems.
  • Challenges and Trade-offs: Cover challenges like network latency, partition tolerance, and the CAP theorem's implications on distributed transactions.

Replication

  • Types of Replication: Describe synchronous and asynchronous replication, their use cases, and trade-offs.
  • Consistency Models: Explain strong versus eventual consistency and their impact on data integrity and system performance.
  • Conflict Resolution: Discuss how conflicts are resolved in multi-master replication scenarios.
  • Replication Topologies: Cover different replication topologies like master-slave, peer-to-peer, and their implications on system resilience and read/write performance.

Auto-Sharding (Data Partitioning)

  • Concept and Benefits: Explain how auto-sharding distributes data across multiple nodes to balance load and improve performance.
  • Shard Key Selection: Discuss the importance of choosing the right shard key for optimal data distribution and access patterns.
  • Rebalancing and Resharding: Cover the process of redistributing data when adding or removing nodes and its impact on system performance.
  • Challenges: Highlight potential challenges such as hotspots and cross-shard transactions.

High Availability

  • Redundancy and Failover: Describe how distributed databases achieve high availability through redundancy and automated failover mechanisms.
  • Load Balancing: Explain load balancing strategies for evenly distributing requests and optimizing resource utilization.
  • Disaster Recovery: Discuss strategies for backup and recovery in distributed environments, including geographical distribution for disaster resilience.
  • Monitoring and Health Checks: Cover the importance of monitoring system health and performing regular checks to ensure high availability.

Cross-Cutting Concepts

  • CAP Theorem: Discuss the CAP Theorem (Consistency, Availability, Partition Tolerance) and its implications for distributed database design.
  • Network Partitioning and Latency: Explain the impact of network issues on distributed databases and strategies to mitigate these effects.
  • Data Consistency Levels: Differentiate between various levels of data consistency (like read-your-writes, monotonic reads, etc.) in distributed systems.
  • Security Considerations: Highlight security challenges unique to distributed databases, including data encryption and secure communication across nodes.

Advanced Topics

  • Global Databases and Multi-Region Deployment: Discuss the architecture and considerations for deploying globally distributed databases.
  • Data Versioning and Time Travel Queries: Introduce concepts like data versioning and the ability to query data as it existed at a specific point in time.
  • Observability and Debugging: Address the complexity of monitoring and debugging in distributed environments, emphasizing distributed tracing and log aggregation.

By covering these topics, you'll provide a thorough understanding of the architectural complexities of distributed databases. These concepts are crucial for anyone looking to design, implement, or manage a distributed database system effectively.