7 Best Change Data Capture (CDC) Tools in 2024

Today, if you are trying to harness the power of up-to-the-minute data, the challenge will be to capture and replicate changes seamlessly across datasets without compromising the performance or integrity of data. 

This is where the best CDC tools, which are modern software solutions, come into play. They are equipped with numerous mechanisms to detect and capture data change, which will ultimately enable you to be more dynamic and responsive.

In this blog, we will deep dive into the features, pros, cons, and pricing of the 7 best CDC tools so that you can make the best choice for your business.

What is Change Data Capture (CDC)?

Change Data Capture, which can also be referred to as CDC, is a process with respect to databases that identifies and tracks any changes that you made to your data. It can replicate this changed data and synchronize it in real-time across multiple systems. CDC propagates the 

updates you made effectively from source to target systems without the need to perform a full scan.

The general need for the CDC is to keep data consistent across a distributed environment for tasks such as data warehousing, business intelligence, and real-time analytics. Since CDC captures only changed data, it minimizes processing overhead and ensures real-time access to the most recent information for downstream systems.

Why do we need CDC Tools?

CDC (Change Data Capture) tools capture and replicate data changes from source databases to target systems in near real-time.

For example, in a retail company, implementing CDC tools was important for maintaining up-to-date inventory levels across multiple stores and online platforms. In this section, we will highlight the importance of CDC tools and why we need them.

• Real-Time Data Replication: The CDC tools capture all changes made to data as they occur in source systems for near real-time replication into target systems. This will enable you to maintain up-to-date data of your organization across multiple systems.
• Minimizes Processing Overhead: The best CDC tools help minimize full table scans or batch processing by capturing only the changed data. It minimizes resource consumption on source databases and improves overall system performance.
• Disaster Recovery: CDC tools can support your business’s continuity since they facilitate rapid failover and recovery strategies.

Benefits of CDC Tools

As you are aware, CDC technologies gather information from several sources and import it into your data warehouse. Why, then, do you require this? For a variety of reasons, is the response.

• Synchronizing replications: The act of tracking changes in a database and capturing them in real-time so that other systems may access the updated data is known as change data capture, or CDC. When real-time updates are required to keep a data warehouse or other downstream systems updated with changes in the source database, data warehousing or data integration scenarios are frequent use cases for CDC.
• Low time consumption: The data warehouse’s data is always up to date as changes made to the transactional database are instantly recorded and transmitted there via CDC.
• Minimized costs: You are proactively cutting expenses when you move data across WANs (Wide Area Networks) since CDC tools only deliver gradual updates.
• Free resources for production: CDC technologies use logs to transport data, and log-based data transfers are incredibly effective ways to load data with the least amount of impact on production resources.
• Reduced strain on the network: CDC technologies free up network capacity by facilitating gradual uploads. CDCs also provide protection against fraud.

What are the Challenges of using CDC Tools?

Challenges	Solutions
Database performance can be affected because CDC operations add more write operations to capture the changes.	You can fine-tune configurations of CDC, like batch size and frequency, to lessen loads on source databases.
Ensuring consistency across a distributed system handling or resolving probable conflicts/discrepancies is challenging.	You can implement timestamp-based conflict detection strategies or application-specific rules in the solution for conflict resolution.
The setup and maintenance of CDC configurations across heterogeneous systems can be a complex job and requires specialized knowledge.	Use CDC tools that have a user-friendly interface and support automation in setup and configuration.

Best CDC Tools

Choosing the best CDC tool that perfectly meets your business requirements can be challenging, especially when a large variety of CDC tools and open source CDC tools are available in the market.

To simplify your search, here is a comprehensive list of the 7 best CDC tools you can choose from and easily start setting up your Data Replication.

1. Hevo Data

Hevo Data is a zero-maintenance platform that allows you to replicate data in near real-time from 150+ Data Sources to the destination of your choice, including Snowflake, BigQuery, Redshift, Databricks, and Firebolt, without writing a single line of code. You can focus on important things and opportunities while we take care of your data for you. So, with Hevo as your data pipeline platform, maintenance is one less thing to worry about.

Key Features

• Pre-Load Transformations: It facilitates pre-load data transformations using Python or an easy-to-use drag-and-drop interface.
• Fault-Tolerant Architecture: Your data is safe even when there is a pipeline failure. Hevo keeps your data in the staging area and notifies you about it.
• Auto Mapping: This is one of the most important features that Hevo provides. Hevo’s schema detection engine automatically detects the schema of the incoming data and by itself creates a compatible schema in the destination.

Pricing Model

Hevo provides transparent pricing that ensures no billing surprises even as you scale. It provides four pricing plans, which are:

• Free:  For moving minimal amounts of data from SaaS tools. Provides up to I M events/month.
• Standard: $ 239/Month – For moving limited amounts of data from SaaS tools and databases.
• Professional: $679/Month – For considerable data needs and higher control over data ingestion.
• Business Critical: You can customize it according to your requirements. For advanced data requirements like real-time data ingestion

You can learn more about our Pricing plans.

Pros

• It is a no-code data platform, so you do not require advanced technical skills.
• It supports Change Data Capture (CDC).
• It also has the ability to perform Reverse ETL.

Let’s look at some of our valuable customer reviews.

“Hevo was the most mature Extract and Load solution available, along with Fivetran and Stitch, but it had better customer service and attractive pricing.”

-Juan Ramos, Analytics Engineer, Ebury

2. IBM Infosphere

IBM Infosphere is a suite of data integration and governance software products developed by IBM.  It is a data integration platform that enables data cleansing, transformation, and data monitoring. It can handle all volumes of data using its highly scalable and flexible data integration platform. Infosphere Information Server provides massively parallel processing (MPP) capabilities.

Key Features

• Master Data Management (MDM): It provides centralized management for master data, providing a ‘single version of truth’ for each key business entity.
• Governance of Data: It has in place policies and mechanisms of control over access management, security, and compliance requirements for data.
• Management of MetaData: It provides data asset cataloging and data lineage tracking to know the origin and relations among the data.

Pricing Model

Their pricing plans are customizable. You can contact their team for details on the price.

Pros

• It is capable of handling large-volume data integration and management requirements across diverse environments.
• It has strong features in data governance, access control, and regulatory compliance.
• It supports integration with various IBM and non-IBM databases.

Cons

• Due to its comprehensive feature set, deployment, configuration, and management of InfoSphere are complex—requiring special skills and resources.
• Licensing and deployment costs can be significantly higher, especially for smaller organizations.
• This could limit flexibility and compatibility with other solutions not from IBM, creating a dependency on IBM’s ecosystem and technology stack.

3. Qlik Replicate (formerly Attunity Replicate)

Qlik Replicate  is a data replication and integration software solution designed for the delivery of real-time data ingestion, synchronization, and streaming between heterogeneous environments. It helps you to replicate data effectively from various sources, such as databases, data warehouses, and streaming platforms, into target systems like data lakes, cloud databases, and analytics platforms.

Key Features

• High-Performance Data Transfer: It enhances the performance of tasks related to data transfer and replication.
• Automated Schema Evolution: It facilitates schema changes to take place in an automated manner to accommodate changes in data structures.
• Real-time Data Replication: It supports real-time data ingestion and synchronization across heterogeneous environments.

Pricing Model

It has four main pricing models that are:

• Starter
• Standard
• Premium
• Enterprise

For details on the exact amount, you can contact them directly.

Pros

• It has flexibility in its wide coverage of sources and targets of data.
• It provides a user-friendly interface with easy setup and configuration tools.
• It includes features of monitoring and management that track the performance of data replication.

Cons

• It requires training and expertise in its more advanced features to optimize performance.
• It may involve frequent updating and maintenance to be at par with the best performance and compatibility.

4. Apache Nifi

Apache NiFi is an open-source data integration and automation tool. It comes with a graphical interface to design data flows and to manage activities between different sources and destinations, meaning it empowers users to collect, route, transform, and process data in real-time, which fits perfectly within data ingestion, transformation, and streaming analytics scenarios.

Key Features

• Built-in Processors: It has a rich set of built-in processors for transforming, enrichment, filtering, and routing of data.
• Data Provenance: Through data lineage and tracking provenance, NiFi provides a way for users to trace data flow originating from its source, through transformation, and into the destination.
• Scalability: It provides support for scalable deployment of software to distributed systems with significant data volumes.

Pricing Model

Apache Nifi is an open-source platform; you do not have to pay to use it. You can use it for free.

Pros

• Active open-source community with continuous development, updates, and contributions.
• Offers flexible routing capabilities based on content, attributes, or conditions.

Cons

• Core functionality customization could be somehow limited unless it was developed from scratch using custom processors or extensions.
• Since it is Java-based, you need to be compatible with Java to use it

5. Oracle GoldenGate

Oracle GoldenGate is end-to-end software that provides real-time integration, replication, and data exchange within heterogeneous systems. It maintains both unstructured and structured data, allowing permanent availability and consistency of data across a wide range of databases, platforms, and cloud environments.

Key Features

• Bi-Directional Replication: This supports bidirectional data synchronization between the source and target systems and enables active-active configurations.
• High Availability and Disaster Recovery: It enables seamless data access and recovery through automated failover and nondisruptive switchover.
• Transformations: It supports data transformation and filtering during replication to accommodate different data formats and structures.

Pricing Model

You can go through all the pricing plans and respective details about the plan.

Pros

• It ensures powerful data filtering and transformation capabilities in data streaming, which consequently allows companies to fine-tune data streams based on specific business needs and requirements.
• It is designed to offer a conflict detection and resolution mechanism if at all these conflicts occur in data due to bidirectional data replication.
• It provides global support and a vibrant ecosystem of partners and consultants.

Cons

• The initial setup cost can be substantial.
• You may face difficulties troubleshooting Oracle GoldenGate during setup or operation.
• It has the possibility to create data latencies in some cases. 

6. Debezium

Debezium is a distributed, open-source platform for change data capture. It comes with a wide array of connectors that simulate streaming in various database transaction logs to a variety of destination systems. Debezium allows for real-time data integration and analysis. 

It captures row-level changes from the database transaction logs of supported databases such as MySQL, PostgreSQL, MongoDB, SQL Server, and others, and then it emits change events, including the data level before and after the change.

Key Features

• Evolution of Schema: It supports automatic schema evolution, capturing any change made to the schema of the database and updating data structures in proper target systems.
• Event-Driven Architecture: It assists in developing event-driven architectures by streaming changes in the database as events, which makes design at the application level reactive and scalable.
• Compatibility with Apache Kafka: It ensures smooth data streaming and processing with the robust, scalable, fault-tolerant Apache Kafka real-time stream integration.

Pricing Model

Since Debezium is an open-source platform, it is free to use.

Pros

• It provides fault tolerance and reliability using Kafka’s distributed architecture in conjunction with the inbuilt resilience features of Debezium.
• It allows integration and synchronization of the data almost in real-time.
• An active open-source community implies innovation, collaboration, and constant improvement.

Cons

• It is dependent on Apache Kafka at the base of its message-passing system.
• If used in a high-volume arena or not kept active, Kafka might let messages stack up in a queue.

7. Apache StreamSets

Apache StreamSets is an open-source, comprehensive platform for developing and managing data pipelines. StreamSets makes it easy to develop data integration workflows with an intuitive graphical interface and several connectors to originate, process, or end data in different systems. StreamSets supports both batch and streaming data processing through the lenses of real-time data integration and data engineering.

Key Features

• Intuitive UI: It has a user-friendly graphical interface for designing, deploying, and monitoring data pipelines without demanding extensive skills from the developer in coding.
• Handles Data Drift: The support of automatic schema drift detection and handling assures that data sources and destinations are always compatible when the pipeline runs.
• Data Quality Management: It contains internal data quality checking, validation, and error handling tools that the user can apply to maintain data-quality rules and manage exceptions properly.

Pricing Model

It has a starting price of $1000 per month.

Pros

• It supports cloud, on-premise, and hybrid deployment to ensure organizations are effectively covered regardless of the infrastructure.
• StreamSets allows dynamic data partitioning based on content, allowing data maximum redistribution across processing nodes while optimizing performance.
• It supports most of the Big Data technologies, including Hadoop and Spark, among many others.

Cons

• Handling errors can become complex.
• Integrating with Legacy systems can be difficult.

Tacking Data Issues With CDC

It’s a good idea to consider the following before choosing the ideal CDC tool for your business:

• Problem solving: Are possible issues settled fast?
• Scale: Is the tool appropriate for every kind of database you use?
• Post-resolution: Is it simple to examine and customize the given solution?
• Support for database topology: Is the instrument adaptable? Is it capable of managing multiple master databases and replicas?
• More connection topologies and SSH tunnels: Is SSH connectivity available? 
• Use cases: Can all use cases, tables, column data kinds, database types, and so forth be handled by the tool?

Choosing the Best CDC Tool

Here are some key factors that you should keep in mind while making your choice for the best CDC tool:

• Check how well the tool aligns with your requirements based on the use case.
• Evaluate how easy it is to integrate the CDC tool.
• Evaluate the complexity of the operations involved in deploying and managing the tool.

Conclusion

In this blog, you went through some of the best CDC tools to implement Change Data Capture. Choosing the right tool among the several Change Data Capture solutions that exist, calls for a subtle understanding of your organization’s requirements regarding data integration. 

The strengths of each tool discussed above will differ. Putting these tools to work in an effective manner will further develop their capability for data integration and insights in real-time while fearlessly assuring data consistency for you. 

“Ready to streamline your data integration? Try Hevo Data today and experience seamless Change Data Capture (CDC) with real-time insights and effortless integration. Start your free trial now and transform how you manage and analyze data!”