Below is a complete, exam-oriented explanation of Server System Architectures in Database Systems.
This topic is part of Parallel Databases / Distributed Systems / DBMS Architecture and is a common 10–15 mark question.

⭐ SERVER SYSTEM ARCHITECTURES

A Server System Architecture defines how a database server is internally structured to process requests, manage data, and interact with clients.
It determines:

How queries are processed
How storage and memory are managed
How concurrency & transactions work
How scalability and parallelism are achieved

Modern DBMS servers are designed to efficiently handle multiple users, high workloads, and large datasets.

Server system architectures are broadly classified into:

Single Server (Monolithic) Architecture
Two-tier & Three-tier Server Architecture
Parallel Server Architectures
Distributed & Multiserver Architecture
Cluster-based Architectures
Classic SMP, MPP, Shared Memory/Shared Disk/Shared Nothing Architectures
Cloud/Virtualized Server Architectures (Modern extension)

Let’s discuss them in depth.

⭐ 1. SINGLE SERVER (MONOLITHIC) ARCHITECTURE

✔ Features:

Entire DBMS runs in a single process
All components (query parser, optimizer, execution engine, storage manager, transaction manager) are inside one server
Uses one CPU or a small number of CPUs
All users connect to the same central database server

✔ Advantages:

Simple design
Easy to maintain
Strong consistency
Ideal for small organizations

✔ Disadvantages:

Limited scalability
Single point of failure
Performance bottleneck with many users

✔ Examples:

Early versions of MySQL, PostgreSQL
Local desktop databases (SQLite)

⭐ 2. CLIENT–SERVER ARCHITECTURE (Traditional Model)

Two main layers:

✔ Client Tier

Provides UI, forms, reports
Sends SQL queries to server
Receives results

✔ Server Tier

Parses queries
Optimizes execution
Manages transactions and concurrency
Maintains data on disk
Sends results back to client

Types:

Two-tier architecture
Three-tier architecture

⭐ 3. PARALLEL SERVER ARCHITECTURES

Parallel server systems are designed to process large amounts of data by using multiple processors simultaneously.

They include:

⭐ A. Shared Memory Architecture (SMP)

All processors share common memory and disk
Fast communication between processors
Low-latency access
Good for small parallelism

Limitation: Memory contention & limited scalability
Examples: SQL Server SMP, Oracle SMP

⭐ B. Shared Disk Architecture

Each processor has private memory
Disks are shared
Requires global lock manager & cache coherence protocols

Advantages:

High availability
Easy failover

Limitations:

Disk becomes bottleneck
Overhead of synchronizing caches

Examples: Oracle RAC, IBM DB2 PureScale

⭐ C. Shared Nothing Architecture (MPP)

Each node has its own disk + memory + CPU
Nodes communicate via high-speed network
Ideal for large parallel processing

Advantages:

Linear scalability
Fault isolation
Highest performance for large data

Examples:

Teradata
Amazon Redshift
Google BigQuery
Greenplum
Cassandra

⭐ 4. DISTRIBUTED SERVER ARCHITECTURE

Database is stored across multiple geographically separated sites.

✔ Types:

Homogeneous Distributed Systems
Heterogeneous Distributed Systems
Federated/Multi-DB Architectures

✔ Features:

Local autonomy
Distributed query processing
Replication & fragmentation strategies
Better reliability and fault tolerance

✔ Use Cases:

Global enterprises
Multi-branch institutions

⭐ 5. CLUSTER-BASED SERVER ARCHITECTURE

Multiple servers work together as a cluster.

✔ Features:

Nodes share workload
Support load balancing
High availability (failover clusters)
Often used in both OLTP and OLAP

Examples:

Oracle RAC
SQL Server AlwaysOn Availability Groups
MySQL Galera Cluster

⭐ 6. CLOUD DATABASE SERVER ARCHITECTURE (Modern & Important)

Cloud DBMS run on distributed cloud infrastructure:

Horizontally scalable
On-demand resource allocation
Managed services (DBaaS: Database-as-a-Service)

Examples:

Amazon RDS
Azure SQL Database
Google Cloud SQL
Snowflake

Features:

Elastic scaling
Distributed storage
Pay-as-you-go model
Automatic backups, patching, failover

⭐ 7. DATABASE SERVER COMPONENT ARCHITECTURE (Internal)

A database server typically consists of these core subsystems:

✔ 1. Query Processor

Query Parser
Query Optimizer
Execution Engine

✔ 2. Storage Manager

Disk manager
File manager
Buffer manager
Index manager

✔ 3. Transaction Manager

Concurrency control manager
Lock manager
Log manager
Recovery manager

✔ 4. Communication Manager

Manages client connections
Implements protocols (TCP/IP, RPC)

✔ 5. Metadata Catalog (Data Dictionary)

Stores schema, tables, indexes, constraints

These components work together inside any database server architecture.

⭐ 8. Comparison of Server System Architectures

Architecture	Scalability	Complexity	Fault Tolerance	Best Use
Monolithic	Low	Low	Low	Small apps
Client–Server	Medium	Medium	Medium	Enterprise DB
Shared Memory	Low–Medium	Low	Medium	OLTP
Shared Disk	Medium	High	High	Clusters
Shared Nothing	High	High	High	Data warehouses/Big data
Distributed DBMS	High	High	High	Multisite DB
Cloud DBMS	Very High	Low (managed)	High	Modern scalable apps

⭐ Perfect 5–6 Mark Short Answer

Server system architectures describe how a DBMS server organizes its processors, memory, storage, and communication roles. Major architectures include:

Monolithic Centralized Servers, where all components run on a single machine.
Client–Server Architecture, where clients send SQL requests and the server processes them.
Parallel Architectures such as Shared Memory, Shared Disk, and Shared Nothing, used for high-performance querying.
Distributed Architectures where databases and computation are distributed across multiple sites.
Cluster and Cloud Architectures, which provide scalability, fault tolerance, and high availability.
These architectures determine performance, scalability, and reliability of a database system.