Comparative Analysis of Azure SQL Data Sync and Read-Only Replicas in Database Management

Summary

Azure SQL Database and Azure Database for PostgreSQL offer two primary data replication solutions: Azure Data Sync and Read-Only replica. While both services facilitate data replication, they serve distinct purposes and exhibit unique characteristics. This post delves into a comparative analysis of Azure Data Sync and Read-Only replica, highlighting their key differences and use cases.

Azure Data Sync Overview

Azure Data Sync is a cloud-based data integration service that enables seamless data replication between multiple sources, encompassing on-premises databases, cloud databases, and SaaS applications. It provides a flexible and customizable approach to data replication, empowering users to configure synchronization schedules, define conflict resolution strategies, and implement data transformation rules.

Key Features of Azure Data Sync:

  • Hybrid data integration capabilities
  • Support for diverse data sources
  • Customizable synchronization schedules
  • Conflict resolution mechanism
  • Data transformation support
  • Bidirectional or unidirectional synchronization

Use Cases of Azure Data Sync:

  • Data migration between on-premises and cloud environments
  • Data consolidation from multiple sources
  • Data warehousing for business intelligence and analytics
  • Real-time data synchronization for critical applications

Read-Only Replica Overview

Read-Only replica is a built-in feature of Azure SQL Database and Azure Database for PostgreSQL that creates a read-only copy of an existing database. It primarily serves the purpose of offloading read-only workloads, such as reporting and analytics, to alleviate the load on the primary database.

Key Features of Read-Only Replica:

  • Read-only copy of an existing database
  • Offloads read-only workloads to improve performance
  • Near real-time synchronization
  • Simple and cost-effective solution

Use Cases of Read-Only Replica:

  • Reporting and analytics on historical data
  • Disaster recovery in case of primary database failure
  • Load balancing to distribute read queries across multiple replicas

Comparative Analysis

FeatureAzure Data SyncRead-Only Replica
PurposeHybrid data integrationOffloading read-only workloads
Supported data sourcesOn-premises databases, cloud databases, SaaS applicationsAzure SQL Database, Azure Database for PostgreSQL
Synchronization typeBidirectional or unidirectionalUnidirectional (read-only)
Synchronization frequencyCustomizable schedulesNear real-time
Data transformationSupportedNot supported
Conflict resolutionCustomizable rulesNo conflict resolution
Use casesData migration, data consolidation, data warehousingReporting, analytics, disaster recovery
ComplexityMore complex configurationSimpler configuration
CostGenerally higher costGenerally lower cost

Replication & Consistency Models

Azure Data Sync utilizes a hybrid replication model, combining asynchronous and synchronous replication methods. Asynchronous replication transfers data between databases without requiring immediate acknowledgement from the destination, allowing for efficient synchronization across large datasets. Synchronous replication, on the other hand, ensures data consistency by requiring the destination database to confirm receipt before proceeding with the next batch of data. Azure Data Sync dynamically adjusts the replication mode based on data volume and network latency to optimize performance and consistency.

Read-Only replica employs asynchronous replication to create a near real-time copy of the primary database. Changes made to the primary database are propagated to the replica periodically, ensuring eventual consistency. This asynchronous approach offers improved performance and scalability, making it suitable for offloading read-only workloads without compromising data integrity.

Here’s a table summarizing the replication and consistency models of Azure Data Sync and Read-Only replica:

FeatureAzure Data SyncRead-Only Replica
Replication modelHybrid (asynchronous and synchronous)Asynchronous
Consistency modelEventual consistencyNear real-time consistency
Data transfer latencyVariable based on data volume and network latencyNear real-time
PerformanceHigh throughput for large datasetsScalable for high read workloads
SuitabilityHybrid data integration, data migration, data consolidationOffloading read-only workloads, reporting, analytics, disaster recovery

Read-only replicas

Read-only replicas are typically implemented using a technique called master-slave replication, where a master database maintains the primary copy of the data and one or more slave databases keep copies of the data. The master database is responsible for writing all changes to the data, and the slave databases are responsible for reading the data from the master database and applying the changes to their own copies.

To test the consistency level of a read-only replica, you can use the following formula:

latency = max(t_master - t_slave)

where:

  • latency is the delay between the time a change is made to the master database and the time it is reflected in the slave database
  • t_master is the time the change was made to the master database
  • t_slave is the time the change was reflected in the slave database

The latency should be as low as possible to ensure that the slave database is an accurate reflection of the master database.

Data sync

Data sync is typically implemented using a technique called change data capture (CDC), where a CDC agent captures changes to the data in a source database and applies them to a destination database. The CDC agent can capture changes in real-time or near real-time.

To test the consistency level of a data sync operation, you can use the following formula:

latency = max(t_source - t_destination)

where:

  • latency is the delay between the time a change is made to the source database and the time it is reflected in the destination database
  • t_source is the time the change was made to the source database
  • t_destination is the time the change was reflected in the destination database

The latency should be as low as possible to ensure that the destination database is an accurate reflection of the source database.

Comparative Summary

FeatureRead-only replicasData sync
Replication modelMaster-slave replicationChange data capture (CDC)
Consistency modelEventual consistencyEventual consistency
LatencyTypically lowCan be higher than read-only replicas
Use casesOffloading read-only workloads, disaster recoveryData migration, data consolidation

Implementation Detail

To establish real-time reporting on your heavily used Azure SQL DB without affecting its performance, you can implement a read-only replica architecture. Here’s a step-by-step guide to setting up read-only replicas and the considerations to keep in mind during implementation:

  1. Create a Read-Only Replica:
    • a. Choose the Replica Location: Select an Azure region that is geographically close to your reporting application to minimize latency.
    • b. Provision the Replica: Using the Azure portal or Azure CLI, create a read-only replica of your primary Azure SQL DB. Specify the desired performance tier and compute units based on your reporting workload.
  2. Connect Reporting Application to Replica:
    • a. Update Connection String: Modify the connection string of your reporting application to point to the read-only replica instead of the primary database.
    • b. Test Connectivity: Verify that your reporting application can successfully connect to the read-only replica and retrieve data.
  3. Monitor Replica Performance:
    • a. Track Replica Lag: Monitor the replication lag between the primary database and the read-only replica to ensure near real-time data availability.
    • b. Adjust Compute Units: If the replica lag exceeds acceptable levels, consider scaling up the compute units of the replica to handle the increased workload.

Considerations during Implementation:

  1. Replication Latency: While read-only replicas provide near real-time data, there is still some latency involved in replicating changes from the primary database. Consider this lag when designing your reporting application.
  2. Replica Costs: Read-only replicas incur additional costs compared to a single primary database. Factor in the cost of the replica when evaluating the overall solution.
  3. Maintenance and Updates: Regular maintenance and updates are required for both the primary database and the read-only replica to ensure optimal performance and security.
  4. Failover Strategy: Implement a failover strategy to ensure continuous reporting even if the read-only replica becomes unavailable. Consider using additional read-only replicas or switching back to the primary database in case of failure.
  5. Data Security: Ensure that access to the read-only replica is restricted to authorized users and applications to protect sensitive sales data.
  6. Monitoring and Alerting: Monitor the health and performance of both the primary database and the read-only replica, and set up alerts to notify you of any anomalies or potential issues.

Azure Tiers

Service TierRead-Only Replicas SupportUse Case
PremiumYesSuitable for applications requiring high-performance, with separated read-only workloads like analytics. Provides automatic primary and secondary replicas.
Business CriticalYesIdeal for critical applications needing high availability and performance, with isolated read-only workloads. Always includes read scale-out feature.
HyperscaleYes (with secondary replica)Best for large-scale, storage-intensive applications. Offers read scale-out with flexible scaling options and workload isolation.
Basic, Standard, General PurposeNo (but similar functionality with geo-replicas or failover groups)Appropriate for less demanding applications that don’t require read scale-out feature but can use geo-replicas or failover groups for similar needs.

Note that Hyperscale is different from the Premium and Business Critical tiers in Azure SQL Database, particularly regarding read-only replicas, due to its unique architecture and capabilities:

  1. Scaling and Performance: Hyperscale offers greater scalability and performance improvements, particularly for large databases. It’s designed to handle larger databases with faster auto-scaling, storage, and compute resources.
  2. Independent Scaling of Replicas: In the Hyperscale tier, secondary replicas, known as named replicas, provide independent scaling. This means you can scale the compute resources of these replicas independently from the primary database, offering more flexibility in managing read-heavy workloads.
  3. Access and Workload Isolation: Hyperscale allows for access and workload isolation between replicas. This is particularly useful for balancing read-only workloads that require more resources than what’s available on a single secondary replica.

In contrast, the Premium and Business Critical tiers automatically provision a primary read-write replica and one or more secondary read-only replicas with the same compute size as the primary. This architecture is less flexible in terms of independent scaling and workload isolation compared to Hyperscale. The focus in these tiers is more on high availability and performance for applications with separated read-only workloads like analytics, without the extensive scalability features of Hyperscale.

Azure Deployment Script

# Set your subscription ID
AZURE_SUBSCRIPTION_ID=YOUR_SUBSCRIPTION_ID

# Set the resource group and server name
RESOURCE_GROUP_NAME=RG-Lab01-Experimental
SERVER_NAME=SQL-Lab01-Experimental

# Set the database name and read-only replica name
PRODUCTION_DATABASE_NAME=ProductionSalesDB
READ_ONLY_REPLICA_NAME=ProductionSalesDBReplica

# Create the production database
az sql db create \
    --resource-group $RESOURCE_GROUP_NAME \
    --server $SERVER_NAME \
    --name $PRODUCTION_DATABASE_NAME \
    --service-level-objective Standard \
    --edition S0

# Insert 50 rows of random data into the production database
for i in {1..50}; do
    az sql db query \
        --resource-group $RESOURCE_GROUP_NAME \
        --server $SERVER_NAME \
        --database $PRODUCTION_DATABASE_NAME \
        --query "INSERT INTO Sales VALUES ('Product $i', RAND(), RAND(), RAND());"
done

# Create the read-only replica of the production database
az sql db replica create \
    --resource-group $RESOURCE_GROUP_NAME \
    --server $SERVER_NAME \
    --name $READ_ONLY_REPLICA_NAME \
    --partner-server $SERVER_NAME \
    --partner-database $PRODUCTION_DATABASE_NAME \
    --service-level-objective Standard \
    --edition S0

# Verify the read-only replica creation
az sql db list-replicas \
    --resource-group $RESOURCE_GROUP_NAME \
    --server $SERVER_NAME \
    --query "[?name == '$READ_ONLY_REPLICA_NAME']"