12 Best CDC Tools(Change Data Capture) for 2026

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 and modern software solutions come into play. They are equipped with numerous mechanisms to detect and capture data changes, ultimately enabling you to be more dynamic and responsive.

In this blog, we will dive deep into the features, pros, cons, pricing, and customer opinions of the 10 best CDC tools available in the market so that you can make the best choice for your business.

What are Change Data Capture (CDC) Tools?

Change Data Capture (CDC) tools are software that detect row-level changes (inserts, updates, deletes) in a source database and immediately deliver those changes to one or more target systems.

They stream only the changed records (not full table reloads) so downstream systems remain synchronised in near real time for analytics, replication, or event-driven apps.

For example, when a customer updates their address in an e-commerce app, a CDC tool instantly replicates that change to the shipping and billing systems, ensuring all services stay up to date.

Note: If you lack the time to review our research, here is a quick comparison table of the best CDC tools to consider.

Benefits of CDC Tools (Change Data Capture)

Data-driven organizations utilize CDC tools for their significant advantages and relevance. Here are some benefits of these CDC tools:

1. Real Time Data Analysis and Business Intelligence

As data continuously changes, it directly impacts reports, making it essential to keep them updated in real time. Live reporting ensures access to the most current and accurate information. Change Data Capture (CDC) synchronizes real-time data, enabling better decision-making based on up-to-date, real-world insights.

2. Data Security & Compliance

Change Data Capture (CDC) offers a powerful approach to managing data securely by maintaining detailed audit trails, tracking data lineage, and documenting changes to critical data sources, essential for meeting regulatory and compliance requirements.

3. Reduced Load on Operational Databases

Change Data Capture (CDC) creates continuously updated replicas of operational databases that can be accessed by various users. By redirecting traffic to these replicated copies, the load on the primary databases is significantly reduced. This minimizes the risk of performance degradation or unexpected downtime on operational databases.

4. Reduced Compatibility Issues When Connecting Multiple Databases

When syncing data from multiple sources, one often faces compatibility issues. CDC overcomes these hurdles by synchronizing data across various cloud environments, on-premise systems, and data stores.

What Are the Best CDC (Change Data Capture) Tools?

To simplify your search, here is a comprehensive list of the 10 best CDC tools for SQL Server CDC, Oracle CDC, MySQL CDC, and more such platforms from which you can choose and start setting up your data replication.

1. Hevo Data

Hevo Data is a cloud-based data platform providing real-time change data capture (CDC) capabilities. It provides more than 150 sources of data and is a completely no-code platform. With Hevo, users can set up custom connectors to ingest data from one-of-a-kind internal or third-party applications, as well as set up REST API or webhooks quickly using Hevo’s simple interface.

Hevo is a multi-tenant platform hosted on AWS and is designed to handle billions of records. Furthermore, Hevo offers two data transformation options: drag-and-drop transformations and Python code-based transformations, which offer users flexibility based on choice.

It is ideally positioned for companies wishing to automate CDC without the requirement of significant technical knowledge or maintenance. Hevo’s target market also consists of companies that require a trustworthy, no-code solution for incremental replication while maintaining data consistency and security.

Key Features

• Monitoring and Alerting: You can monitor your CDC pipeline health with intuitive dashboards showing every pipeline stat and data flow. You also get real-time visibility into your CDC pipeline with alerts and activity logs.
• Automated Schema Management: Whenever there’s a change in the schema of the source database, Hevo automatically picks it up and updates the schema in the destination to match.
• Security: Hevo complies with major security certifications such as HIPAA, GDPR, and SOC-2, ensuring data is securely encrypted end-to-end.
• 24×7 Customer Support: Live chat with around-the-clock assistance and thorough support documentation is available.

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 1 M free events/month.
• Starter: $ 239/Month – Moving limited 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

• Hevo is a no-code data platform, so you do not require advanced technical skills.
• Designed to manage updates, patches, and scaling effectively, ensuring consistent uptime and optimal performance.
• Smart Assist feature in Hevo proactively displays any error or condition that could affect the data ingestion in your CDC Pipelines.
• Quality assessments ensure that your data changes are registered accurately.

What I like best about Hevo Data is its intuitive user interface, clear documentation, and responsive technical support. The platform is straightforward to navigate, even for users who are new to data migration tools. I found it easy to set up pipelines and manage data flows without needing extensive technical support. Additionally, Hevo provides well-organized documentation that clearly explains different migration approaches, which makes the entire process smooth and efficient.

Henry E.

Software Engineer

2. Fivetran

Fivetran is a leading data integration platform built on the principle of Change Data Capture (CDC).  Fivetran is powered by HVR following its acquisition in 2021. Fivetran HVR reads directly from the database transaction logs to capture just the changes, like inserts, updates, and deletes, as they occur. HVR supports CDC on numerous platforms, including Oracle, SQL Server, PostgreSQL, and SAP HANA.

Fivetran also provides enterprise-level security and governance capabilities. In addition, the entire data integration process is completely managed and serviced by Fivetran’s global customer support, which is available 24/7/365 and has a guaranteed uptime of 99.9%.

If you are looking for a secure system with strong data governance policies and anticipate heavy data volumes in your CDC pipeline, then Fivetran is your ideal tool.

Key Features

• Automated Schema Management: Automatically detects and adapts to changes in source schemas, ensuring seamless data integration without manual intervention.
• Vast Library of connectors: Features an enormous library of 700+ connectors with a distributed architecture.
• Flexible capture methods: Though log-based CDC is the default option, HVR supports flexibility using other capture methods, including: Trigger-Based Capture, Archive Log Only (ALO), and Direct Redo Access (exclusive to Oracle databases).

Pricing Model

Fivetran offers four pricing plans: Free, Standard, Enterprise, and Business Critical. Pricing is based on Monthly Active Rows (MAR) and plan features. Fivetran has recently changed its pricing model. Check out Fivetran Pricing Model Update for a detailed insight.

Pros

• Minimal setup with automated pipeline management.
• Wide range of connectors for SaaS applications and databases.
• Scalable for high-volume data processing.

Cons

• Limited customizability for unique use cases. (Source)
• Inconsistent schema delivery across customers, requiring complex standardization scripts.
• Pricing may become challenging as data usage scales. (Source)

Customer Testimonial

Most of the older connectors are reliable -- consistent data, a consistent data delivery schedule, easy setup, implementation, and integration.

Eric A.

Chief Data Officer

3. Airbyte

Airbyte is an open-source data integration software that supports log-based CDC. It uses Debezium as an embedded library to capture and monitor changes in your database. Airbyte also provides AI-assisted functionality, which reads through your API documentation and autofills the configuration fields while setting up the CDC pipeline.

One of the unique features of Airbyte is the ability to build custom connectors using their Connector Development Kit (CDK), in addition to the 550+ pre-built connectors that Airbyte provides. Currently, Airbyte supports log-based CDC from Postgres, MySQL, and Microsoft SQL Server to any destination, such as BigQuery or Snowflake.

So, if you are an open-source enthusiast looking for an AI-supported CDC tool with excellent community support, then Airbyte is your go-to platform.

Key Features

• Flexibility to Develop Python CDC Pipelines: Through PyAirbyte, Airbyte’s open-source Python library, users can develop and manage CDC pipelines in Python.
• Structured and Unstructured Sources: Airbyte supports both structured and unstructured data sources, as well as vector database destinations, making it an ideal solution for AI use cases.
• Self-Managed Enterprise Features: The self-managed enterprise edition of Airbyte provides the capabilities to gain full control over your sensitive information with features like role-based access control.
• Metadata Tracking: Automatically tracks change metadata (e.g., ab_cdc* columns) to maintain data lineage and facilitate accurate updates.

Pricing Model

Since Airbyte is an open-source platform, it is free, whereas Airbyte Cloud offers usage-based pricing. 

Pros

• Airbyte has an active community support on GitHub and Slack.
• 550+ open-source structured and unstructured data sources.
• Highly flexible with customizable connectors.

Cons

• Requires technical expertise for self-hosting.
• Data must be in tables, not views.
• The open-source version has limited real-time syncing
• CDC incremental is only supported for tables with primary keys.

Customer Testimonial

I really appreciate that Airbyte is open-source and comes with a wide range of pre-built connectors. The UI is intuitive, and the platform makes it easy to configure data syncs. I also like how frequently updates and improvements are made by the team and the community.

Aniruddh S.

Indigo Squad Member

4. Qlik Replicate (formerly Attunity Replicate)

Qlik Replicate is a data replication and CDC platform that is specifically built to cater to the needs of today’s analytics environments. Qlik provides an agentless, log-based approach to change data capture. 

It allows companies to handle and transfer data across various systems in an efficient manner with low latency by persistently capturing and providing changes from various data sources. 

Key Features

• High-Performance Data Pipelines: Stream high-speed, real-time data from any source to any target.
• Automated Schema Evolution: Adapts to changes in data structure automatically.
• Real-Time Data Replication: Supports live data ingestion and synchronization across varied environments.

Pricing Model

Qlick typically follows an enterprise pricing model.

Pros

• Broad support for diverse source and target systems.
• User-friendly UI with a low-code setup.
• Built-in monitoring and performance tracking tools.

Cons

• Requires training to optimize advanced features.
• Frequent updates may be necessary for performance and compatibility.
• Unclear error messages and weak documentation. (Source)
• If a connection is lost, a full reload is required. (Source)

Check out our latest article on Fivetran vs Qlik

Customer Testimonial

Our data integration process was simplified, and both its ease of use and the manner in which it transfers data from one place to another had a good influence on our performance.

Neel Shah

Head Android Engineer

5. Skyvia

Skyvia is a cloud-based, no-code CDC platform designed to simplify data workflows for businesses of all sizes. Skyvia allows users to connect SaaS applications, databases, and cloud data warehouses without deep technical expertise. 

Skyvia ensures that transactions are captured and delivered in their original order and applied to the target exactly once. This maintains data integrity and consistency between source and target systems. Skyvia offers optimized CDC mechanisms for cloud-native databases and managed database services, considering their operational constraints.

If you are using a cloud native database, Skyvia could be a great option.

Key Features

• No-Code, User-Friendly Interface: Enables setup and management of data pipelines without coding.
• Comprehensive Data Integration: Supports ETL, ELT, Reverse ETL, migration, and sync.
• Extensive Connector Library: Offers 200+ built-in connectors, enabling use cases like Salesforce Change Data Capture (CDC), and connections for BigQuery, Redshift, SQL Server, and more.
• Automation & Workflow Management: Built-in scheduling and automation tools.

Pricing Model

Skyvia uses a flexible freemium model:

• Free Tier: 5,000 records/day and basic scheduling.
• Paid Plans: Start at $19/month, with scalable options up to $999/month depending on volume and features like mapping templates and unlimited packages.

Pros

• Easy-to-use no-code interface.
• Flexible integration options.
• Broad connector support.

Cons

• Processing speed could be improved.
• Queue handling may introduce delays.

Customer Testimonial

Customer support is generally very responsive and helpful. The no-code setup is also pretty intuitive, especially if you have prior experience with creating data flows. Failure notifications via email also mean that you don\'t need to keep too close an eye on automated integrations.

Samuel A.

Data Analyst

6. Debezium

Debezium is an open-source distributed platform designed for Change Data Capture (CDC). It facilitates debezium CDC real-time data migration by capturing row-level database changes and outputs them as an Apache Kafka stream. This makes it well-suited for building scalable, fault-tolerant streaming data pipelines and real-time data replication, a common pattern for Kafka CDC implementations.. By capturing database transaction log changes as events, Debezium facilitates real-time synchronization between source and target systems.

Debezium stands out as a powerful CDC tool due to its flexibility, low-latency streaming, and ability to handle various database sources such as MySQL, PostgreSQL, SQL Server, and MongoDB. Additionally, Debezium itself is used as the core platform for many other CDC tools. 

If you are looking for a legacy system with a strong fault-tolerant service, Debezium is your go-to tool.

Key Features

• Real-Time Streaming: Integrates with Apache Kafka for real-time change streaming.
• Schema Change Handling: Automatically adjusts to schema updates in source databases.
• Event-Driven Architecture: Emits changes as structured events for reactive design.

Pricing Model

Debezium is fully open-source and free to use. For their premium services, kindly visit their official site.

Pros

• Utilizes Kafka’s distributed design for strong fault tolerance.
• Enables real-time data integration and synchronization.
• An active, open-source community ensures constant innovation.
• Supports reactive system design with event-based streaming.

Cons

• Dependent on Apache Kafka for message passing.
• Message queue build-up may occur in high-volume scenarios if Kafka is not actively managed.

7. AWS Database Migration Service

AWS provides the Database Migration Service (DMS), which facilitates smooth database replication. It has Change Data Capture (CDC) support to replicate changes continuously throughout the process of migration. 

DMS preserves data consistency in real-time with minimal downtime. The service has broad support for the most widely used database engines, making migration simple and quick for any platform.

AWS DMS is great for organizations that are already working in AWS environments. Apart from that, if you are looking for a reliable cloud-based CDC, DMS is a great tool.

Key Features

• Support for Multiple Database Engines: AWS DMS supports popular database engines like Oracle, SQL Server, PostgreSQL, MySQL, MongoDB, MariaDB, and more, offering flexibility in migration across various platforms.
• Serverless Option with AWS DMS Serverless: The serverless model automatically provisions, scales, and manages resources, making migrations easier and eliminating manual configuration.
• Versatile Sources and Targets: AWS DMS supports migrations from both on-site and cloud-hosted databases, offering source and target environments flexibility.

Pricing Model

AWS DMS provides multiple hourly pricing options based on resource usage. For specific pricing details and customized options, you can contact the AWS team.

Pros

• Easy to set up and user-friendly for database migrations.
• Minimal downtime and real-time replication.
• Backed by detailed documentation and responsive AWS support.

Cons

• Change Data Capture (CDC) is challenging to implement and requires a detailed understanding and additional effort to set up correctly.
• Sometimes, users must manually input data into JSON, which can become complicated and messy.
• The pricing can be higher, especially when migrating large amounts of data or during long-term use. (Source)

Customer Testimonial

We used this service to migrate the DB from 3CX to the AWS cloud, which was very convenient with a user-friendly interface, and the support received was quite quick.

Ashish R.

Zoho CRM

Check out our AWS DMS guide for a deeper dive and to learn more about AWS DMS CDC in detail.

8. Azure Data Factory

During the 2023-2024, Azure Data Factory (ADF) added native support for Change Data Capture (CDC) as a first-class resource within the Azure Data Factory studio. This feature lets users set up continuously running jobs for real-time data processing. ADF has two supported forms of CDC: the incremental column method and the database-maintained change log method. The incremental column method picks one column for detecting changes, while the database-maintained change log method uses the internal change logs maintained by the database, making it an automated change tracking solution without extra columns for identification.

Azure Data Factory’s CDC capability supports various data sources and destinations for seamless data movement across hybrid environments. The supported sources are Azure SQL Database, SQL Server, Snowflake, Azure Cosmos DB, and others such as JSON, Parquet, and XML. Targets supported are various destinations like Azure Synapse Analytics, SQL Managed Instance, Delta, and others.

Organizations already using the Azure platform can leverage the CDC integration of Azure Data Factory.

Key Features

• Mapping Data Flows: A graphical, code-less environment. It accommodates CDC operations without coding.
• Integration Runtime: Scalable and elastic compute infrastructure that handles data movement and transformation activities between cloud and on-premises environments.
• Hybrid Connectivity: Allows seamless connectivity to cloud-based and on-premises data sources, giving enterprises maximum flexibility with hybrid data environments.
• Real-Time Data Movement: Facilitates real-time data replication and transaction processing and maintains current synchronization between data sources and destinations.

Pricing Model

Azure Data Factory employs a pay-as-you-go pricing model, whereby you pay only for what you consume. Payments are based mainly on the volume of pipeline runs, data flow execution times, and the number of data movement operations.

Pros

• User-friendly interface with drag-and-drop pipeline design.
• Includes built-in activities for efficient CDC operations.
• Integrates easily with other Azure services for end-to-end solutions.

Cons

• Limited Support for Complex Transformations. (Source)
• Certain operations are limited, such as restrictions on data types beyond Int32.
• Costs can increase quickly, especially with frequent pipeline runs or large data volumes, if not adequately monitored.
• Logging and monitoring capabilities are relatively basic and may not provide sufficient detail for advanced troubleshooting.

Customer Testimonial

I am happy to use ADF. ADF just needs to add more connectors with other third-party data providers. Also, logging can be improved further.

Rajesh Y.

Manager, Enterprise

9. Striim

Striim provides a low-impact, real-time change data capture (CDC) capability to stream database changes (inserts, updates, and deletes). Striim provides continuous data ingestion from databases and other sources in real time using Streaming SQL.

Striim supports high-performance log-based CDC for a variety of databases, including Oracle database, SQL Server, MySQL, HPNonStop, and MariaDB. Striim also supports non-database sources, including files, logs, messaging systems (Kafka), IoT devices, data warehouses, and more. Striim also provides CDC template wizards to automate the creation of applications that leverage change data capture. Apps created with templates can be modified using Flow Designer, another feature of Striim.

If you are looking for a dynamic tool that can automatically create your CDC pipeline using their CDC templates, without putting in much technical effort, Striim would be a reliable tool for you.

Key Features

• Robust In-Network Checkpoints: These checks guarantee data validity and provide users with confidence that their data is safe.
• Pre-built integration applications: Striim allows users to define how they want to receive the stream of change events in their CDC application.
• Flexible Data Flow Design: Create and connect intricate data flows graphically or programmatically through the UI with Striim’s TQL scripting, supporting dynamic and scalable stream processing.
• AI-Ready Output: Converts incoming data to JSONL format, which is ready for OpenAI ingestion and model training.

Pricing Model

Striim offers different pricing editions, ranging from $4,400 to $20,000 per month. The Striim Cloud Enterprise Platform starts at $4,400/month for every 100 million events. A free trial is also available, allowing users to explore the platform before committing.

Pros

• Ingests data from databases, applications, and IoT devices.
• Quickly deploys and scales across Striim clusters with minimal effort.

Cons

• Users indicate that the documentation is unclear and therefore more difficult to follow.
• The interface is not user-friendly, and users tend to have a difficult time navigating or locating major features. (Source)
• The cost of licensing is deemed high relative to other equivalent tools, with ideas of improved value or elastic costs.
  

Customer Testimonial

There are two main use cases that Striim was taking our interest in: It is the platform itself, and it provides you the kitchen for your data, regardless of the kind and format it is. Change data capture is the key feature that is natively supported for mainstream RDBMS used in our premises.

Verified User

Manager in Information Technology

10. IBM InfoSphere

IBM InfoSphere Data Replication, CDC is a solution that captures database changes as they happen, also known as Db2 Change Data Capture, and delivers them to target databases, based on table mappings that are configured in the Management Console of InfoSphere Data Replication.

Apart from the common targets and destinations like MySQL, Postgres, Redshift, etc, InfoSphere allows you to send data from a Db2 database on z/OS to other supported databases like Oracle or SQL Server, and vice versa. Front-end functionality for InfoSphere CDC for z/OS is provided through the Management Console. 

Management Console allows you to work with tables and databases in source and target environments to configure, start, and monitor replication. Infosphere’s Admin API operates as an optional Java-based programming interface that you can use to script operational configurations or interactions.

InfoSphere CDC is intended for organizations that want to replicate Db2 data to or from a z/OS system. 

Key Features

• Master Data Management (MDM): Centralized data management for a single source of truth.
• Robust front-end functionality: Helps to facilitate the management of tables and databases in both source and target environments. 
• Data Governance: Robust control over data access, security, and compliance.
• Metadata Management: Offers data lineage and cataloging tools.

Pricing Model

IBM InfoSphere provides custom pricing and is available for on-premise installations. There are three plans for their deployments: Small, Medium, and Large, with pricing starting at $19,000 per month.

Pros

• Strong governance, access control, and compliance features.
• Integrates with both IBM and non-IBM databases.
• It provides massive parallel processing (MPP) capabilities.

Cons

• Complex setup and management process.
• Higher costs, especially for smaller organizations.
• Dependency on IBM’s ecosystem for compatibility.

Customer Testimonial

Very easy to configure and manage. Very easy to migrate to new environments. Very stable. It is not user-friendly when using through UI.

Atiq R.

Senior Consultant DBA

11. Oracle GoldenGate

Oracle GoldenGate is a real-time data replication and integration platform that enables CDC and transactional data movement across heterogeneous systems. It is designed to capture committed transactions (both DML and DDL) from source systems using log-based methods.

Oracle GoldenGate captures committed database changes directly from transaction logs using the Extract process. These changes are written to trail files, which serve as a durable, platform-independent record. Optionally, a Data Pump moves these trail files to the target system.

Oracle GoldenGate is distinguished by its ability to support real-time transactional replication with minimal source database overhead, leveraging log-based capture rather than batch extraction.

Key features:

• Heterogeneous database support: The tool supports replication across diverse databases, Oracle, MySQL, PostgreSQL, SQL Server, DB2, and more, allowing seamless integration across hybrid and multi-cloud environments.
• Log-based architecture: By reading directly from transaction logs instead of querying live tables, GoldenGate minimizes overhead on production databases and ensures transactional accuracy and performance.
• Deployment options: It supports multiple replication topologies such as unidirectional, bidirectional, cascading, and hub-and-spoke. The microservices architecture enables deployment on-premises, in the cloud, or as containerized services.

Pricing Model:

The OCI service is priced per OCPU per hour.

Pros:

• Deep integration with Oracle database logging and security layers.
• Scalable architecture with parallel processing and high throughput.
• Sub-second latency for data movement across systems.

Cons:

• Some users report slower vendor support and update cadence.
• Steep learning curve for configuration and management.
• Administration and monitoring complexity can be significant.

Oracle Golden gate has eased so many complication that an employer faces, be it in relation with payroll, absences or anything, it helps in making the transactions easier using the technology in its best way.

Syeda Sana S.

Functional Consultant

View Review

12. Talend

Talend CDC is an enterprise-grade CDC solution that monitors and captures database transactions (inserts, updates, deletes) from source systems and propagates them to target systems in near real-time.

Talend CDC stores captured changes in dedicated change tables and publishes them to subscribers for defining target endpoints. The subscribers then apply only the deltas to targets such as Snowflake, Kafka, or S3.

Talend CDC stands out for its broad database support, multiple capture modes, and flexible delivery options. Its ability to stream deltas to various destinations, from relational databases to modern data lakes, makes it suitable for both on-premises and cloud architectures.

Key features:

• Multi-mode change capture: Talend supports both trigger-based and log-based CDC, letting users choose the method that best fits their source system’s performance and configuration.
• Seamless integration: CDC integrates directly into the Talend Data Fabric, enabling unified management of data quality, transformation, and governance. This integration streamlines pipeline orchestration and simplifies monitoring.
• Centralized monitoring: Talend provides centralized dashboards to configure, track, and manage CDC jobs. Users can monitor replication status, identify bottlenecks, and ensure continuous, reliable data flow across all connected systems.

Pricing Model:

Talend provides four customizable pricing tiers: Starter, Standard, Premium, and Enterprise, with costs based on the features and capabilities selected.

Pros:

• Drag-and-drop visual workflow designer with code support.
• Strong community, documentation, and support resources.
• Vast connector ecosystem, over 1,000 sources and targets supported.

Cons:

• Some users experience slow UI or high memory usage.
• Performance may degrade on large data volumes.
• The setup of CDC across all databases can be complex.

Why is it Essential to have a Change Data Capture Tool?

CDC tools are essential in modern data ecosystems for the following reasons:

1. Real-Time Data Replication 

They capture and replicate changes in real time, ensuring up-to-date information across all connected systems.

2. Minimises Processing Overhead

 Only incremental changes are captured instead of full scans or heavy batch jobs, reducing strain on source systems.

3. Disaster Recovery

 CDC enables reliable failover and recovery mechanisms by ensuring the latest data is always backed up or replicated.

What are the Challenges of Using CDC Tools?

Challenges	Solutions
CDC operations can impact database performance due to added write operations.	Fine-tune batch size and sync frequency to reduce load on source databases.
Maintaining consistency across distributed systems and resolving conflicts can be complex.	Use timestamp-based conflict resolution or application-specific reconciliation logic.
Configuration and maintenance across diverse systems is often complex.	Choose CDC tools that offer automation, intuitive setup, and good documentation.

Factors to Consider Before Choosing A Change Data Capture (CDC) Tool

Criteria	Description	Recommended Tools
Integration Type (Batch vs. Real-Time)	Determine whether your use case requires batch, real-time, or hybrid CDC. Real-time CDC helps maintain data consistency with minimal lag.	Batch: Hevo, Fivetran, Qlik Replicate Real-Time: Debezium
Ease of Use & Technical Expertise	Consider how user-friendly the tool is, and whether it requires coding or offers a no-code/low-code experience for quicker onboarding.	User-Friendly: Hevo, Fivetran, Qlik Replicate Developer-Focused: Debezium, Airbyte
Security & Compliance	Evaluate if the tool supports secure data transmission, encryption, authentication, and compliance with data protection standards.	High Security: Azure Data Factory, AWS Database Migration
Database Compatibility	Ensure compatibility with your source and target databases (SQL, NoSQL, cloud/on-prem). Broader support ensures flexibility.	Broad Support: Qlik Replicate, Fivetran, Debezium, Hevo
Scalability & Future Growth	Choose a tool that can grow with your organization and maintain performance with increasing data volumes.	Highly Scalable: Fivetran, Hevo
Target System Support	The CDC tool should integrate seamlessly with your analytics systems, data lakes, and warehouses (e.g., Snowflake, Redshift, BigQuery).	Versatile Targets: Hevo, Qlik Replicate, Fivetran
Transformation Capabilities	Determine if the tool supports data enrichment or transformation during or post-ingestion to match your analytics needs.	Advanced Transformation: Hevo, Fivetran
Deployment Flexibility	Decide whether the tool supports cloud, on-prem, or hybrid deployment based on your IT infrastructure.	Cloud-Only: Hevo, Fivetran Hybrid: Qlik Replicate
Performance Optimization	Look for tools that deliver consistent performance under high throughput or system load to avoid bottlenecks.	Optimized Performance: Hevo, Qlik Replicate
Data Integrity & Reliability	Ensure the tool guarantees accurate, consistent, complete data replication, even during failure recovery.	High Reliability: Qlik Replicate, Debezium
Community, Support & Learning	Choose a tool with good documentation, an active user community, or responsive technical support.	Strong Community: Debezium, Airbyte Enterprise Support: Qlik Replicate, Hevo
Cost Structure	Consider your budget. Open-source tools are cost-effective but may need more management; managed services offer ease at a premium.	Cost-Effective: Hevo, Debezium, Airbyte Premium Services: Qlik Replicate, Fivetran, Striim

Conclusion

Choosing the right change data capture tool requires deeply understanding your business needs and data architecture. Each tool has unique strengths that can cater to specific use cases.

Effective implementation of CDC tools enables change tracking, seamless data integration, real-time analytics, and operational efficiency, while ensuring accuracy and consistency.

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 14-day free trial now and transform how you manage and analyze data!

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