Tutorial: Scale out Azure SQL Database

This tutorial guides you through the process of scaling out your Azure SQL Database. Scaling out involves distributing your data and workload across multiple database instances to improve performance and availability. We will cover strategies for sharding, implementing distributed transactions, and managing your scaled-out solution.

Introduction to Scale-Out Strategies

Scaling out, also known as horizontal scaling, is a critical technique for handling increasing data volumes and user loads. Unlike scaling up (vertical scaling), which involves increasing the resources of a single server, scaling out distributes the workload across multiple smaller, independent units.

For Azure SQL Database, common scale-out patterns include:

  • Sharding: Partitioning your data across multiple databases based on a sharding key.
  • Elastic Pools: A cost-effective solution for managing and scaling multiple databases with varying and unpredictable usage demands.
  • Database Partitioning (within a single database): For very large tables, you can partition data within a single database to improve query performance.

Prerequisites

  • An Azure subscription.
  • An existing Azure SQL Database server.
  • Basic understanding of SQL and database concepts.

Step 1: Planning Your Sharding Strategy

Choosing the right sharding key is crucial. Consider these factors:

  • Cardinality: The key should have a high number of unique values.
  • Query Patterns: Queries should ideally target specific shards to minimize cross-shard operations.
  • Data Distribution: Ensure data is evenly distributed to avoid hot spots.

Common sharding keys include User ID, Tenant ID, or a Geographical identifier.

Step 2: Implementing Shards

You can create multiple Azure SQL Databases to act as your shards. For example, if you are sharding by 'TenantID', you might create databases like:

  • myDatabase_Shard1 (for TenantIDs 1-100)
  • myDatabase_Shard2 (for TenantIDs 101-200)
  • myDatabase_Shard3 (for TenantIDs 201-300)

You will also need a catalog database to keep track of which shard holds which data range.

Step 3: Application Logic for Routing

Your application will need to intelligently route queries to the correct shard. This typically involves:

  1. Looking up the sharding key in the catalog database to determine the target shard.
  2. Establishing a connection to the appropriate shard.
  3. Executing the query.

Important Consideration: Cross-Shard Transactions

Managing transactions that span multiple shards can be complex. Azure SQL Database supports distributed transactions, but they introduce overhead. For optimal performance, try to design your application to perform operations within a single shard whenever possible.

Step 4: Using Elastic Pools for Managed Scaling

Elastic Pools offer a simpler way to manage multiple databases that have variable usage patterns. Instead of allocating dedicated resources to each database, you group them into a pool and share resources. This is particularly useful for SaaS applications with many tenants.

To set up an elastic pool:

  1. Navigate to your Azure SQL Database server in the Azure portal.
  2. Select "Elastic pools" from the left-hand menu.
  3. Click "Create pool".
  4. Configure the pool settings (e.g., name, region, performance characteristics).
  5. Add your existing databases to the pool.

Step 5: Monitoring and Performance Tuning

Once your database is scaled out, continuous monitoring is essential. Use Azure Monitor and SQL Server tools to track:

  • CPU, memory, and I/O utilization per shard.
  • Query performance and identify bottlenecks.
  • Connection pooling and latency.
  • Shard distribution and balance.

Regularly review your sharding strategy and adjust as your application's needs evolve. You may need to rebalance shards or migrate data between them.

Further Reading