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CDC Replication: What It Is, How It Works, & Use Cases

From financial institutions ensuring real-time transaction updates to massive enterprises synchronizing vast amounts of information across continents, CDC replication is the backbone of streamlined data flow. It is the reason your online shopping cart knows exactly when an item is out of stock or why your banking app reflects your latest transactions almost instantly.

Before putting Change Data Capture (CDC) replication into action, it is crucial to understand how it works and where it fits in. Skipping this foundational understanding causes data discrepancies, synchronization issues, or worse – information gaps that disrupt critical processes.

Over the next few minutes, we will explore CDC replication in detail and talk about its different types, benefits, and use cases. We will also discuss how tools like Timeplus can further augment CDC strategies for your business.

What Is CDC Replication?

CDC Replication - What Is CDC Replication

CDC replication is a specialized method of copying data between 2 databases in real or near real-time. Unlike other data replication techniques, CDC specifically targets and replicates only the newly added or modified data. This makes it much more efficient than techniques like snapshot replication, where complete snapshots of a database are repeatedly moved. 

While snapshot replication is ideal for preserving individual data snapshots over time, it requires extensive processing resources and can be costly. CDC replication, on the other hand, offers a more efficient and cost-effective alternative for real-time data processing needs​​.

With CDC replication, you can efficiently capture and process data changes as they occur, particularly in an SQL database like Postgres, MySQL, and SQL Server database.

How Does CDC Replication Work?

CDC replication operates by monitoring and recording database events. When changes occur in a source database, CDC replication identifies them without a full database scan, which is a major advantage as it reduces the load on the database server.

The CDC process involves a few key steps:

  • Change identification: The CDC system keeps an eye on the database logs or employs triggers to spot any new changes like data insertions, updates, or deletions.

  • Change capturing: Once a change is identified, the CDC system records it. This capturing of changes is done in a way that reflects the exact change made to the database.

  • Change logging: The captured changes are then logged into a separate data store or a change table. This table holds details about the changes, including the type of change and the time it occurred.

  • Change propagation: Finally, these logged changes are transferred to the target system or database. This ensures that the target database table remains in sync with the source table.

While the general steps in any CDC replication remain the same as we discussed above, not all CDC systems work on the same principles. To understand this, let's discuss the 3 types of CDC systems.

3 Types Of CDC Replication

CDC replication can be carried out in various ways. In each of these change data capture methods, the goal remains the same: to efficiently and accurately capture data changes for various applications like real-time analytics, data warehousing, or database migration. 

The choice will depend on your specific requirements like the database environment, performance considerations, and the level of detail needed in capturing data changes.

A. Log-Based CDC

CDC Replication - Log-Based CDC

Log-based CDC works by monitoring the database transaction log. All databases record every change, like inserts, updates, or deletes, in the transaction logs. This type of CDC taps into this log to capture changes. This makes log-based CDC highly efficient for tracking database modifications without adding extra load to the database.

Advantages Of Log-Based CDC

  • As changes occur, they are immediately logged for quick database replication.

  • Log-based CDC captures all types of database changes, including schema modifications and data updates.

Disadvantages Of Log-Based CDC

  • Log-based CDC requires in-depth knowledge of the database’s logging mechanism.

  • Different databases have unique logs so you need customized approaches for each.

B. Trigger-Based CDC

CDC Replication - Trigger-Based CDC

This method employs database triggers, which are special procedures that are automatically executed in response to certain events in the database. These triggers are set up on tables that need monitoring. When data in a table changes, the trigger is activated to capture this change.

Advantages Of Trigger-Based CDC

  • Triggers operate in real-time, capturing changes as they happen.

  • It allows specific capture and processing of data changes based on defined triggers.

Disadvantages Of Trigger-Based CDC

  • Setting up and maintaining triggers requires careful planning and monitoring.

  • Triggers can add significant load to the database which can slow down operations.

C. Timestamp-Based CDC

CDC Replication - Timestamp-Based CDC

This method relies on timestamp or datetime columns in your database tables. It tracks changes based on the time they occur, which is recorded in these specific columns. This way, it can recognize and include only the rows with recent timestamps in the CDC data.

Advantages Of Timestamp-Based CDC

  • Since this method is based on periodic checks, it places less strain on the database.

  • Timestamp-based CDC is easier to implement compared to log-based or trigger-based methods.

Disadvantages Of Timestamp-Based CDC

  • Timestamp-based CDC is not suitable for scenarios requiring immediate data replication.

  • This method is only effective in databases where timestamp fields are reliably used and updated.

5 Proven Benefits Of CDC Replication

CDC replication ensures that your data is a true asset for your business and lets you use data for real-time decision-making, maintaining system efficiency, and providing accurate insights – all while being scalable and adaptable to your changing needs. Let’s discuss in detail the major benefits of using CDC replication in your data systems.

1. Real-Time Data Availability

CDC Replication - Real-Time Data Availability

Real-time data availability is the foundation of CDC replication and this can change how your business interacts with its data. When data changes occur, CDC replication guarantees that the changes are immediately reflected in the target system. This is crucial for dynamic environments where timely information is key to staying ahead.

For instance, in financial markets, real-time data can help in quick trading decisions for increased profitability. Similarly, in retail, understanding customer behavior instantly can drive immediate promotional strategies. 

The key point is that real-time data is an essential tool for businesses to stay competitive and proactive. CDC plays a major role in ensuring this data is rapidly and effectively delivered to where it is most needed.

2. Minimized Impact On Source Systems

Traditional data extraction methods require heavy system resources which can cause slowdowns. CDC replication, on the other hand, quietly and efficiently captures data changes with minimum impact on source systems. 

This is particularly important for businesses that operate 24/7, like eCommerce platforms or global services, where system availability and performance are non-negotiable.

3. Data Accuracy & Integrity

CDC replication systems are engineered with a strong emphasis on data accuracy and integrity and this offers major benefits. CDC systems ensure that the data in your analytics or reporting tools is the most current and accurate reflection of your source systems.

This is important for businesses where data drives critical decisions, like healthcare or logistics. In these sectors, even minor inaccuracies cause serious consequences. The data integrity also means that you can maintain regulatory compliance more easily, as you are always working with the most recent data snapshot.

4. Enhanced Data Analysis & Reporting

Enhanced data analysis and reporting capabilities are direct outcomes of CDC replication. With up-to-date and accurate data at your fingertips, your analysis tools can churn out more relevant and timely insights. This can help discover new business opportunities or identify potential threats more quickly. 

For instance, in marketing, real-time data can help understand customer trends and tailor campaigns more effectively. In manufacturing, it can cause better supply chain optimization by analyzing current data patterns.

5. Scalability & Flexibility

As your data volumes grow or your business needs change, CDC replication can scale to meet these new demands without major overhauls. This scalability is essential for rapidly growing businesses experiencing rapid growth or undergoing digital transformation

Flexibility is also seen in CDC’s compatibility with various data sources and targets, making it an ideal choice for businesses that use a mix of legacy systems and modern applications.

5 Use Cases Of CDC Replication

Let’s discuss 5 areas where CDC replication can significantly impact your operations:

I. Data Warehousing

CDC Replication - Data Warehousing

CDC replication plays a key role in keeping your data warehouses or data lakes updated in near real-time. As transactions occur and data changes in the source OLTP databases, CDC captures these changes and streams them incrementally to the data warehouse. 

Since CDC streams data changes continuously, there is no need to define rigid batch windows when the warehouse can be loaded. This avoids restricting operational processes.

Using CDC for moving data to a warehouse also lowers costs by transferring only changes. When only change data is streamed across the network, it saves bandwidth and compute costs associated with repeatedly extracting and loading entire data sets after each batch window.

II. Real-Time Analytics

Continuously capturing change data events allows the CDC to feed real-time analytics platforms to drive actions based on what is happening at that moment. This lets you make faster, more informed decisions – a capability that is vital in areas like financial trading or emergency management. 

Some more specific use cases include:

  • You can set up alerts and notifications based on specific change data events. For example, an SMS alert can be sent when inventory drops below a threshold or when a VIP customer places an order.

  • With CDC, you can stream change data into real-time dashboards that can use this data to generate live views of your business KPIs. As operational metrics change, dashboards update automatically without delay.

  • Real-time data coming into your data processing system can be used for rapid detection of anomalies, cybersecurity threats, and fraudulent activities. This way, issues can be flagged immediately before they escalate.

III. Database Migration

When migrating operational databases, you have to maintain business continuity. CDC replication lets you efficiently replicate data from old to new systems with minimal downtime

It preserves the integrity and accuracy of your data during this crucial process, ensuring that no critical information is lost and that the existing data in the source databases remains unaffected by the replication operations. It works by:

  1. Taking an initial snapshot of the source database and syncing it to the target database.

  2. Capturing ongoing changes from the source database and applying them to the target via CDC processes.

This keeps both databases synchronized during the transition period. By streamlining the cutover process, CDC allows uninterrupted operations with zero or minimal downtime when migrating databases.

IV. Master Data Management

CDC Replication - Master Data Management

In master data management, CDC replication helps you achieve a consolidated and accurate view of your essential business data. Capturing data changes continuously ensures that your master data is always current and reliable, which is vital for decision-making and regulatory compliance. 

This involves the following steps:

  1. Identify which data store will serve as the authoritative master data source.

  2. CDC will then capture any inserts, updates, and deletes from this store.

  3. These change events are streamed to downstream systems needing access to master data.

With this approach, the latest, accurate master data is available across the organization. CDC makes this process happen in near real-time while also avoiding full data reloads.

V. Cloud Integration

For businesses transitioning to the cloud, CDC replication is a must. It helps seamless data synchronization between on-premises and cloud-based systems which is crucial for maintaining a consistent data environment across both platforms. 

More specifically, CDC replication can help you in the following 2 use cases related to cloud data storage:

  • Cloud migration: CDC’s incremental data approach minimizes network bandwidth during migrations since only change data goes across the network.

  • Hybrid environments: CDC can sync cloud databases with on-premises systems by continuously capturing and applying data changes bidirectionally between the 2. 

5 CDC Replication Best Practices

When you start incorporating CDC replication into your systems, following established strategies will ensure an efficient and secure replication process. Let’s discuss these best practices that should always be a part of your routine whenever you use CDC replication.

i. Comprehensive Data Mapping

It is crucial to accurately map data from the source to the target system in CDC replication. This involves identifying all relevant data fields and establishing clear mapping rules. 

Comprehensive data mapping guarantees data integrity and data consistency and helps with smoother data integration and replication. Consider data types, formats, and structures to ensure the replicated data accurately reflects the source data. Whenever you use CDC, make sure to:

  • Identify all relevant data fields.

  • Establish clear rules for how each field is mapped.

  • Account for differences in data types, formats, and structures.

This will help you maintain the consistency and accuracy of your replicated data.

ii. Robust Error-Handling

Effective error-handling mechanisms are essential in CDC replication. This includes detecting errors, logging them, and implementing strategies to resolve issues without disrupting the replication process. 

When you are developing the error handling system for your data systems, make sure it can:

  • Detect and log errors as they occur.

  • Carry out automated recovery strategies to resolve issues seamlessly.

  • Set up alerts for immediate notification of any replication issues.

This will help keep the system running smoothly and maintain the reliability of your CDC replication process.

iii. Performance Monitoring

Regularly monitoring the CDC replication process is also vital to maintain optimal performance. This helps identify and address bottlenecks or inefficiencies and ensures that the replication process remains efficient and does not overload the source or target systems. 

To keep your CDC replication process optimized, make sure to:

  • Identify and address any performance bottlenecks.

  • Regularly monitor KPIs like latency, throughput, and resource usage.

  • Adjust resource allocation as needed to avoid overloading your systems.

Monitoring helps in maintaining an efficient replication process and prevents system overloads.

iv. Security Measures

Since CDC replication transmits data between systems, implements access controls, encryption in transit and at rest, VPNs, VLANs, and other measures to secure the data stream. To guarantee data security, you must:

  • Encrypt data during transmission.

  • Implement strict access controls and authentication mechanisms.

  • Regularly update and audit your security protocols to comply with current data privacy standards.

This will protect your data from unauthorized access and potential breaches.

v. Regular Testing & Validation

Lastly, make regular testing and validation part of your routine to:

  • Conduct tests for data integrity and replication accuracy.

  • Simulate failover scenarios to maintain system resilience.

  • Regularly compare source and target data to validate replication fidelity.

These validation steps are crucial in catching discrepancies early and ensuring that your CDC replication process stays accurate and reliable.

Timeplus & CDC Replication

CDC Replication - Timeplus

Timeplus is a powerful streaming-first data analytics platform, designed to handle real-time as well as historical data processing demands. Its architecture is tailored to handle massive sets of streaming data with ultra-low latencies of less than 5 milliseconds. It can also handle over 10 million events every second even on standard hardware. 

This speed and adaptability make Timeplus a top choice for real-time analytics and ideal for CDC replication. Let’s take a closer look at how Timeplus can help you with CDC replication:

a. Efficient Real-Time Data Processing

Timeplus offers a high-performance streaming SQL engine. This engine can process data changes as they occur, with high efficiency and low latency. This ability is crucial in CDC replication where timely data processing is essential.

b. Integration With Various Data Sources

A core strength of Timeplus is its compatibility with a variety of data sources. It can seamlessly connect to platforms like Kafka, Pulsar, Amazon S3, and Amazon Kinesis. These sources are often used in CDC replication, making Timeplus a versatile tool in diverse data environments.

c. Support For Changelog Stream

Besides supporting platforms like Kafka and Pulsar, Timeplus also supports CDC using Changelog Streams. It can work with established CDC solutions like Debezium and offers flexibility. If your applications can produce events in a specific format, Timeplus can manage these directly. This capability lets Timeplus adapt to different CDC methodologies, giving you comprehensive data change tracking options.

d. High-Performance Storage & Analytics

Besides capturing and processing data in real-time, Timeplus is also equipped for high-performance storage and analytics. This design enables the platform to handle large volumes of change data which is a common challenge in CDC replication.

e. Real-Time Visualization & Dashboards

Timeplus’s capability extends to real-time visualization and dashboarding. This feature is particularly useful in a CDC pipeline as it allows you to monitor and analyze change data in real-time. This immediate insight into data changes can drive quicker business decisions and responses.


As technology advances and we gather more data, the importance of CDC replication grows. The sheer speed and accuracy it offers in syncing data across various platforms can affect how well a company can keep up in fast-changing markets. Those using CDC replication have the advantage of being agile, responsive, and staying ahead of their competitors.

However, while the possibilities are exciting, actually setting up an effective CDC pipeline takes real expertise. From change data capture mechanisms to data mapping and security protocols, you have to address many technical complexities.

This is where a tool like Timeplus can make all the difference. With its high-speed streaming architecture optimized for processing real-time data events, Timeplus can take care of the crucial workload in your CDC pipeline. Its versatility also allows connecting to existing infrastructure like Kafka or database logs while maintaining optimal performance.

So if you are looking to unlock the potential of change data, Timeplus is the ideal platform to build upon. To learn more about how Timeplus can revolutionize your CDC replication strategy, sign up for a demo today or start your free trial.



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