1. Introduction to Distributed Database Design
A Distributed Database (DDB) is a collection of interrelated databases distributed across different physical locations but connected via a network. The design of a distributed database involves careful planning to ensure efficient data storage, access, and management across multiple sites while maintaining data integrity, consistency, and performance.
Why is Distributed Database Design Important?
✅ Ensures efficient data distribution for better performance.
✅ Reduces data redundancy while maintaining consistency.
✅ Improves fault tolerance and availability in case of failures.
✅ Enhances query optimization by reducing data transfer costs.
✅ Supports scalability for growing applications.
2. Steps in Designing a Distributed Database
The design of a distributed database consists of several key steps:
1. Requirements Analysis
- Identify business needs and data access patterns.
- Define types of transactions (e.g., read-heavy, write-heavy).
- Determine geographic distribution of users.
✔ Example:
- A global e-commerce website requires customer data stored near regional offices for faster access.
2. Data Distribution Strategy
The data must be distributed efficiently to improve performance and availability. The three main strategies for distributing data are:
A. Fragmentation (Partitioning)
- Splits a large database table into smaller fragments.
- Each fragment is stored at a different site based on access patterns.
🔹 Types of Fragmentation:
| Type | Description | Example |
|---|---|---|
| Horizontal Fragmentation | Divides tables by rows (records) | Customers in Asia stored in one server, and customers in Europe in another. |
| Vertical Fragmentation | Divides tables by columns (fields) | Customer names and emails stored in one site, and addresses in another. |
| Hybrid Fragmentation | Combination of both horizontal & vertical | Customers in Asia have only essential columns stored locally. |
✔ Example of Horizontal Fragmentation in SQL:
CREATE TABLE Customers_US AS
SELECT * FROM Customers WHERE Country = 'USA';
✅ Reduces query load by storing data closer to the users.
B. Data Replication
- Copies of data are stored at multiple sites.
- Ensures fault tolerance and high availability.
- Types of Replication:
- Full Replication: Entire database copied to every site.
- Partial Replication: Only frequently accessed data is copied.
- Synchronous Replication: Changes are updated instantly across all sites.
- Asynchronous Replication: Updates occur after some delay.
✔ Example: Replicating Data for Faster Access
CREATE TABLE Orders_Replica AS
SELECT * FROM Orders;
✅ Ensures faster order processing.
C. Data Allocation
- Decides where to store fragments or replicas.
- Types of Allocation:
- Centralized: Data stored in one central location.
- Partitioned: Each site stores different parts of the data.
- Replicated: Some or all data is duplicated across sites.
✔ Example:
- Banking System
- Customer transactions stored locally at branches.
- Loan data stored in regional data centers.
- Reports and analytics stored in central servers.
3. Distributed Database Architecture
The design of a distributed database follows different architectures:
1. Client-Server Architecture
- Clients send requests to a central database server.
- The server processes queries and returns results.
✔ Example: A banking app where clients access a centralized database.
2. Peer-to-Peer Architecture
- Each node acts as both a client and a server.
- Used in blockchain and decentralized applications.
3. Multi-Database (Federated) Architecture
- Multiple independent databases are integrated under a global schema.
✔ Example: A global airline system integrating multiple airline databases.
4. Query Processing in Distributed Databases
Efficient query execution is essential in a distributed system.
Challenges in Distributed Query Processing
❌ Data is spread across multiple sites – queries may need to fetch remote data.
❌ Network delays – large data transfers slow down queries.
❌ Data consistency issues – updates must be synchronized.
✔ Example: Distributed Query Execution
SELECT Customers.Name, Orders.OrderID
FROM Customers JOIN Orders
ON Customers.CustomerID = Orders.CustomerID
WHERE Customers.Region = 'Europe';
✅ Optimized query execution fetches only required data from European servers.
5. Distributed Transaction Management
Transactions must follow ACID properties across multiple sites.
Two-Phase Commit Protocol (2PC)
- Ensures all sites commit or rollback together.
- Phase 1 (Prepare): All sites check if they can commit.
- Phase 2 (Commit/Rollback): If all sites agree → Commit. Otherwise → Rollback.
✔ Example: Distributed Bank Transfer
1️⃣ Deduct $500 from Account A (USA Server).
2️⃣ Add $500 to Account B (UK Server).
3️⃣ If both succeed → Commit, else → Rollback.
✅ Ensures no partial transactions occur.
6. Security in Distributed Databases
✔ Access Control: GRANT and REVOKE privileges to specific users.
✔ Data Encryption: Encrypt data before transmission.
✔ Authentication: Secure login mechanisms.
✔ Audit Logs: Monitor database access.
✔ Example: Granting Read-Only Access
GRANT SELECT ON Customers TO 'read_user'@'localhost';
✅ Prevents unauthorized modifications.
7. Advantages and Disadvantages of Distributed Database Design
✅ Advantages
✔ Improved Performance – Data stored closer to users.
✔ Scalability – Easily add more nodes.
✔ Fault Tolerance – Replication prevents data loss.
✔ Flexibility – Supports global businesses with multiple locations.
❌ Disadvantages
❌ Complex Management – Requires careful planning and administration.
❌ Data Synchronization Issues – Updates across sites must be handled efficiently.
❌ Security Risks – More nodes = more vulnerabilities.
❌ High Setup Cost – Needs advanced networking and multiple servers.
8. Conclusion
🔹 Distributed database design focuses on data fragmentation, replication, and allocation to optimize performance and availability.
🔹 Uses query optimization and transaction management to ensure data consistency and reliability.
🔹 Despite challenges, it is widely used in banking, cloud storage, e-commerce, and global enterprises.