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Database architecture

Database architecture is the overall design of how a database system is structured and how its components work together to store, process, and retrieve data. It defines the layers (such as storage, query processing, and application interfaces), the data organization (schemas, tables, indexes, constraints), and the comm

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  1. Database Architecture

    Database architecture is the overall design of how a database system is structured and how its components work together to store, process, and retrieve data. It defines the layers (such as storage, query processing, and application interfaces), the data organization (schemas, tables, indexes, constraints), and the communication paths between clients and the database engine.

  2. Common Architectural Patterns

    Typical architectures include: - Single-tier: applications connect directly to the database engine. - Client–server: clients send queries to a centralized database server. - Multi-tier: applications, services, and the database are separated for scalability and maintainability. - Distributed databases: data is partitioned across multiple nodes (sharding) and replicated for availability. Key decisions include consistency model (e.g., strong vs. eventual consistency), replication strategy, partitioning method, and how transactions are handled across components.

  3. Key Components and Design Goals

    A well-defined architecture covers: - Data model: relational (tables/joins), document, key–value, graph, or hybrid. - Storage and indexing: how data is physically stored and how indexes speed up queries. - Query and transaction processing: optimization, concurrency control, and isolation levels. - Security: authentication, authorization, encryption in transit/at rest, and auditing. - Performance and reliability: caching, connection pooling, backup/restore, monitoring, and disaster recovery. - Scalability: vertical scaling, horizontal scaling, and operational procedures for growth.

FAQ

What is the difference between database architecture and database schema?

Architecture describes the system’s overall structure and components; schema is the specific logical design of data (tables/collections, relationships, constraints).

How do replication and sharding affect architecture?

Replication improves availability and read performance; sharding distributes data to scale writes and storage, but adds complexity for queries and consistency.

What should I consider for choosing an architecture?

Workload patterns (reads vs. writes), required consistency, latency targets, expected data growth, operational constraints, and security/compliance needs.

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