If you’re relying on data that’s hours or even minutes old, you’re already at a disadvantage.
That’s why real-time Change Data Capture (CDC) platforms are gaining popularity. CDC solutions capture and stream changes from your source databases in real time, sending them to targets such as data warehouses and data lakes. This log-based, low-latency data streaming method avoids the overhead and delays of full data extractions, giving you faster analytics and helping you make decisions you can trust.
Traditional batch-based ETL (Extract, Transform, Load) processes can’t keep up. Batch jobs run on fixed schedules—often taking hours or even days to deliver data to its destination—leaving both you and your intelligent systems and AI applications a step behind. With CDC, pipelines stream updates in near real time to relational databases (like SQL Server or Oracle), data warehouses, data lakes, or other targets, so your organization’s leaders can react in the moments that matter most.
For these reasons, CDC tools have grown from a niche market technology to an essential solution. They’re used across industries and company sizes, from high-growth startups needing real-time analytics to large enterprises modernizing legacy systems. The right CDC strategy empowers you to keep up with exponential data growth, achieve sub-second latency, and modernize aging ETL architecture.
Which CDC platform is right for your enterprise? This guide compares leading CDC solutions—Striim, Confuent, Fivetran, Oracle GoldenGate, and Qlik Replicate—so you can evaluate which features, connector coverage, latency capabilities, and pricing will work best for your needs.
What Is Change Data Capture (CDC)?
Change data capture (CDC) is a method for identifying and capturing changes—such as inserts, updates, and deletes—in your databases and replicating them downstream. Instead of relying on full reloads, CDC continuously streams only the new or modified data,
CDC tools capture changes in several ways. Query-based and trigger-based approaches exist, but they can be intrusive and place additional load on your source systems. Log-based CDC is the most robust and scalable method because it reads directly from database transaction logs, creating low latency, data freshness, and non-intrusiveness.
Adopting log-based CDC lets you synchronize data in near real time without impacting production workloads. This makes it possible to act on data the moment it’s created, powering operational dashboards, advanced analytics, machine learning models, customer-facing applications, and event-driven use cases. Keep reading to learn common CDC use cases and discover the key features to look for in a CDC tool.
Why You Should Use CDC Tools
Legacy data architectures and siloed information can slow down your enterprise’s ability to use real-time analytics and leverage AI. Change data capture (CDC) tools break down these barriers by continuously streaming changes from source systems to cloud data warehouses (Redshift, Snowflake, BigQuery), data lakes, streaming platforms, and data lakehouses (Databricks).
Pain Points Addressed by CDC Tools
With a modern data architecture backed by CDC, you can solve these longstanding challenges.
Legacy Architectures Can’t Support Modern Data Demands. Traditional batch-based ETL pipelines, siloed systems, and cobbled-together point solutions (such as Debezium + Kafka + Flink) introduce complexity, delay innovation, and hinder AI adoption. CDC tools modernize data pipelines by giving your enterprise continuous, trusted, and enriched data.
AI Initiatives Are Stalled by Stale or Inaccessible Data. Current enterprise data infrastructure fails to deliver the velocity or reliability required for advanced use cases. Real-time CDC pipelines remove data silos and deliver continuous, fresh data, giving your AI models, generative AI applications, and real-time decisioning models enriched and trusted data with sub-second latency.
Data Teams Are Overburdened by Tool Sprawl and Maintenance. Managing and maintaining separate CDC, transformation, and delivery tools strains your engineering resources and overwhelms your teams. Tool sprawl also slows project timelines and increases total cost of ownership (TCO). Best-in-class change data capture platforms consolidate CDC with streaming, delivery, and observability, delivering faster time to value and reducing TCO.
Inconsistent governance increases risk. When sensitive data flows through pipelines without real-time direction, masking, or lineage, it creates audit gaps and non-compliance with frameworks like HIPAA, GDPR, and SOC2. CDC platforms provide integrated masking, lineage tracking, and anomaly detection, enriching your enterprise’s data compliance and governance strategies.
Business stakeholders lack timely insights. Missed Service Level Agreements (SLAs), failed ETLs, and long recovery windows create blind spots across your finance, operations, and customer experience teams. Modern data streaming tools provide real-time dashboards, replacing once-a-day refreshes with fresh updates.
Digital transformation efforts carry operational risk. Unreliable, poorly integrated batch tools hinder cloud migrations and platform re-architecture initiatives. Reliable, observable CDC tools enable zero-downtime cloud migrations and multi-cloud synchronization without disrupting your daily operations.
Data accessibility and freshness are compromised. Change data capture platforms keep your enterprise’s data fresh, accurate, and available, building trust in analytics and helping you accomplish aspirational mission-critical initiatives like fraud detection, and hyper-personalization.
Reducing Risk, Maintaining Compliance
Managing your organization’s risk profile in today’s fraught cybersecurity environment and keeping up with regulations are two challenges that keep IT teams up at night.
Understand why real-time data is an essential element for both.
Key Benefits of CDC Tools
As the engine behind modern streaming data pipelines, CDC platforms fundamentally shift your organization’s ability to put data to good use. Rather than simply moving data, CDC unifies it across your organization, creating real-time intelligence that drives faster decisions and impacts every part of the business.
Greater success with AI and analytics initiatives: AI models rely on the freshest possible data. The longer the delay or lag, the less relevant the contributions of an AI system. With best-in-class CDC platforms, enterprises can power real-time analytics and sophisticated, AI-driven applications from the same data stream, deploying LLMs that actually work.
Reduced complexity and lower TCO: Maintaining separate tools for CDC, stream processing, enrichment, and delivery adds cost and complexity. By consolidating these capabilities into a single platform, you can reduce engineering overhead, cut licensing costs, and ease operational burdens, freeing up your teams to focus on meaningful projects.
Improved governance and compliance posture: Enterprise-ready CDC solutions will support your organization’s governance requirements. This includes implementing access controls, maintaining detailed audit trails, and encrypting data both in transit and at rest. Platforms like Striim include Sentinel AI and Sherlock AI to spot and secure sensitive information as it moves, protecting it from unauthorized use. These built-in governance features also make it easier for your enterprise to pass audits for standards such as HIPAA, GDPR, and SOC 2.
Stronger business agility and scalability: CDC tools enable your teams to launch new data products, build AI pipelines, and deliver live operational insights quickly, without rebuilding infrastructure or compromising resilience. CDC provides the agility to scale data operations and keep up with the growth of your business.
Trusted, always-on data for leadership and frontline teams: Trusted, always-on data changes the way everyone works across your enterprise. Key stakeholders can monitor KPIs, track consumer behavior, assess operational risks in the moment, and make critical decisions with confidence.
The Foundation for AI
Is your data architecture limiting your ability to effectively implement generative AI? Most enterprises (74%) struggle to implement AI effectively because they lack real-time, trusted data. CDC changes the equation by fundamentally transforming how data flows through your business, giving you the foundation for AI.
Common Use Cases
CDC tools can power a wide range of operational and analytical use cases, from real-time analytics to application-level intelligence. By delivering a continuous stream of fresh data, CDC solutions give you new ways to move faster and gain deeper insights.
Streaming transactional data from OLTP to cloud data warehouses: With CDC, you can stream real-time transactional updates directly from online transaction processing (OLTP) systems, such as relational operational databases, into your cloud data warehouses. Log-based CDC preserves ACID transaction integrity while avoiding the performance impact of repeated full-table queries. This ensures your downstream analytics platforms and BI tools always work with the freshest possible data.
For example, global payments company Clover consolidated its fragmented infrastructure by streaming data from 23 MySQL databases into Snowflake in real time, reducing operational complexity and empowering developers to take on higher-value tasks.
Real-time fraud detection and personalization using CDC and streaming: When you need to react instantly, whether to catch fraud, personalize customer experiences, or right-size inventory, CDC combined with in-flight stream processing gives you an edge. You can merge transactional, behavioral, and third-party data in real time, apply continuous queries, and trigger actions as soon as anomalies appear.
In banking, this might mean automating fraud prevention by flagging suspicious transfers before they complete. In retail, it could mean achieving personalization at scale by adjusting offers based on a customer’s live browsing behavior.
Zero-downtime cloud migration or multi-region sync: Downtime during a migration breaks customer experiences, increases compliance risks, and can even cost revenue. With CDC, you can replicate on-prem databases to cloud targets without interrupting live applications. After the initial load, CDC keeps both on-prem and cloud-based systems in sync until cutover, ensuring no data is lost and no service is disrupted. This same principle applies when you need multi-region or multi-cloud synchronization. CDC keeps geographically distributed systems in lockstep to support global scalability and disaster recovery strategies.
Triggering workflows and alerts based on specific change events: CDC lets you turn raw change data into action. By defining rules or conditions on change streams, you can automatically send alerts, update downstream systems, or kick off remediation steps when specific changes occur. This event-driven approach underpins fraud detection, IoT monitoring, operational dashboards, and more, essentially turning your data pipeline into a live control system for your business.
Rethinking Customer Experiences
Real-time analytics are remaking the customer experience. Companies can now use data to transform the way they understand user preferences and deliver on those priorities.
Learn how some businesses are increasing first-call resolutions, reducing repeat calls, and boosting customer ratings.
Top Change Data Capture Tools Compared
CDC tools vary widely in architecture, capabilities and, naturally, maturity. To choose the right one, you need to understand the key features that set today’s most effective CDC solutions apart.
Key features
- Best-in-class real-time CDC capabilities with sub-second replication, preserving data integrity and supporting high-throughput workloads
- Built-in SQL-based stream processing for transforming, filtering, enriching, and joining data in motion
- An all-in-one platform that eliminates tool sprawl, lowers TCO, and accelerates time to value
Best fit
Large, data-intensive enterprises in financial services, retail/CPG, healthcare/pharma, hospital systems, travel/transport/logistics, aviation, manufacturing/energy, telecommunications, technology, and media
Pros
- Purpose-built for enterprise-scale CDC
- AI-powered data governance features
- Natively real-time from the ground up
Cons
- Initial learning curve (mitigated by dedicated customer success teams and robust training resources, including Striim Academy)
Pricing
- Free trials available for Striim Developer (perfect for learning and small-scale use cases) and Striim Cloud (fully managed, horizontally scalable streaming)
- Contact sales for pricing on Striim Platform (self-hosted deployments on your infrastructure)
Key features
- Broad CDC connector ecosystem, including log-based and query-based connectors (Debezium, JDBC, and more)
- Publishes database changes into Apache Kafka event streams for downstream processing
- Stream governance and tooling for secure, compliant, event-driven CDC pipelines
Best fit
Organizations that want to be based on Kafka
Pros
- Real-time data propagation for analytics and automated workflows
- Enterprise-grade governance and pipeline management
- Supports databases, mainframes, and cloud deployments with rich connector choices
Cons
- Costly pricing structure with usage-based charges that can stack up quickly
- Requires deep Kafka expertise and complex setup
- Operational overhead and a fragmented ecosystem of unnecessary add-ons
- Users reported throughput issues with certain CDC connectors such as Oracle
Pricing
- Basic (free) plan with usage limits
- Paid tiers with usage-based pricing. Fully managed connectors incur fees per-task-hour charges
Key features
- Library of pre-built connectors for SaaS, databases, and apps
- Log-based and incremental CDC that captures deletes and incremental updates and reliably tracks progress
- Type 2 SCD support, column hashing, data blocking, and full/partial resyncing options
Best fit
Small-medium organizations
Pros
- Fully managed pipelines with minimal setup
- Extensive connector ecosystem ensures broad source compatibility
- Strong governance, transformations support, and batch resiliency
Cons
- Pricing can be unpredictable and costly for multi-connector deployments
- CDC isn’t real-time for all sources; sync intervals can introduce lag
- Some users report reliability issues, including breaks, delays, and limited transparency.
Pricing
- 14-day free plan is available, though connector triggers may vary
- Usage-based pricing for paid tiers
Key features
- Heterogeneous, real-time replication across multiple database types with exactly-once delivery
- Log-based CDC with minimal impact on source systems
- Flexible integration, staging databases, and evolving schema support
Best fit
Large organizations with data replication needs
Pros
- Proven reliability for mission-critical replication with MAA certification
- Wide support for targets, databases, and hybrid/multi-cloud technologies
- ICLI, GUI, APIs, and integration with Oracle Data Integrator (ODI) and Oracle Cloud Infrastructure (OCI)
Cons
- Requires specialized expertise to deploy and maintain
- Licensing can be costly, especially standalone or with add-on modules
- Some connectors are difficult to configure or debug
Pricing
- Free trial plus Free 23ai and Studio Free options
- Paid tiers licensed per core or instance; add-ons increase costs
Key features
- Agentless, log-based CDC
- High-performance, scalable data pipelines
- Centralized GUI and monitoring console for managing thousands of replication tasks
Best fit
Companies looking to unify high-volumes of data
Pros
- Fast, reliable real-time CDC with minimal source system overhead
- Supports legacy, on-prem, cloud, and streaming targets
- Strong management interface and automation capabilities
Cons
- GUI and support portal weakness, as noted by users
- No transparent pricing
- Complexity can grow at enterprise scale
Pricing
- Free trial available
- Pricing on request only
Key Features to Look for in a CDC Tool
Change data capture (CDC) works by continuously monitoring your databases for changes, capturing them instantly, and supplying them as event streams to other systems or platforms. Whenever one of your users acts, the database logs it as an INSERT, UPDATE, or DELETE event. A CDC platform connects directly to your database to identify these changes in real time.
You can detect changes in different ways, including by polling tables for timestamp modifications, triggering database events when updates occur, or reading directly from transaction logs.
Each approach comes with trade-offs in performance, delay, and complexity. Evaluating these differences is essential to selecting the most suitable CDC tool for your organization.
Log-Based Change Capture
Log-based CDC is the gold standard for modern data integration. This technique reads changes directly from your database’s native transaction log (e.g., the redo log in Oracle or the transaction log in SQL Server). Because every database transaction is written to this log to ensure durability and recovery, it serves as a complete, ordered, and reliable record of all changes.
The key advantage of log-based CDC is its non-intrusive nature. It puts almost no load on the source database because it doesn’t execute any queries against the production tables. It works by “tailing” the log file, similar to how the database itself replicates data. Log-based CDC is highly efficient and scalable, capable of capturing high volumes of data with sub-second latency. Some log-based CDC tools come with the ability to analyze different tables to ensure replication consistency.
This reliability and low-impact approach is why modern, enterprise-grade streaming platforms like Striim are built around a scalable, streaming-native, log-based CDC architecture.
Real-Time Data Delivery
Your CDC tool should move data instantly to downstream systems, whether it’s your analytics platform, operational dashboard, or event-driven applications. By streaming changes as they occur, you can power analytics, migration workflows, synchronization, and other downstream processes without waiting for batch schedules.
Broad Source and Target Support
Choose a platform that connects to all the places you need, including relational databases, NoSQL stores, cloud data warehouses, data lakes, messaging systems, and more. A platform with broad support makes it easy for you to plug CDC into your current tech stack, connect to new systems as your needs grow, and stay flexible for whatever comes next.
Schema Evolution Handling
Your data isn’t static, and your pipelines shouldn’t be, either. Columns get added, types change, tables get renamed. You need a CDC solution that adapts without breaking your data flows. Modern platforms detect schema changes, propagate them downstream, and notify you when schemas drift, keeping your pipelines safe and your data reliable.
Built-In Stream Processing
Many CDC tools just capture changes. Advanced platforms take it a step further with SQL-based stream processing that lets your users filter, transform, enrich, and join data in motion—before it ever reaches a warehouse, dashboard, or operational system. Think of it as a real-time data refinery, delivering analytics-ready streams that accelerate time to insight.
Fault Tolerance and Exactly-Once Delivery
You need your data to be reliable every time you query it. A strong CDC platform ensures exactly-once delivery, using checkpoints and automatic error recovery to prevent duplicates or missing updates. This kind of reliability is critical for finance, compliance, and other sensitive workloads.
Monitoring and Observability
The best CDC tools give you dashboards, logs, metrics, and alerts so you can track throughput, latency, schema changes, and errors. With full visibility, you can monitor pipeline health so you can troubleshoot faster, prevent issues, and stay ahead of problems.
Deployment Flexibility (Cloud, On-Prem, Hybrid)
Your CDC platform should work where you work, whether it’s on-premises, in the cloud, or across a hybrid setup. Seek platforms that can adapt to your infrastructure so you can scale, re-architect, or migrate without having to replace your platform later.
Change Data Capture Tools in Action
Track database updates, inserts, and deletes in real-time with Change Data Capture to power data replication and migration. Learn more about CDC tools and use cases.
How to Choose the Right CDC Tool for Your Needs
With so many options available, navigating the CDC vendor landscape can be challenging. Narrow the field and create a focused shortlist of viable vendors by looking closely at these three areas.
Evaluate Total Cost of Ownership (TCO)
Determining the TCO goes beyond licensing fees. You should also consider the engineering resources you’ll need to build and maintain CDC pipelines, the need for third-party tools like Kafka or stream processors, and the platform’s ability to scale up or across clouds without costly re-architecting.
Look for Key Features of Modern Platforms
Seek solutions that embrace the features that matter most to your enterprise, including these must-haves:
- Log-based change capture for efficient, low-impact extraction of database changes
- Real-time data delivery to keep analytics and applications continuously updated
- Broad source and target support, enabling flexible integration across diverse environments
- Schema evolution handling to adapt automatically as data structures change
- Built-in stream processing for filtering, transformation, and enriching data in motion
- Fault tolerance and exactly-once delivery, ensuring data integrity without duplicates or loss
- Monitoring and observability to track pipeline health and resolve issues quickly
- Deployment flexibility across cloud, on-premises, and multi-cloud environments
These features will help you choose a robust, scalable CDC platform that will generate meaningful ROI.
Ask Strategic Questions
Once you identify the best CDC solutions, it’s time to evaluate vendors. Focus on these critical errors to ensure the solution can meet your technical requirements and business goals.
- Data source and target compatibility: Does the tool support log-based CDC for your specific database version? What about future migration targets?
- Latency and throughput underload: Can the solution handle high-volume changes in near real time without data loss or degradation?
- Streaming enrichment: Do you need to transform or filter data in flight?
- Error handling and recovery: What happens when a target is unreachable? Can the CDC platform retry, checkpoint, and resume?
- Operational visibility: How easy is it to monitor, alert, and audit pipeline performance?
- Security and compliance: Is the CDC platform compliant with your governance model (SOC2, HIPAA, etc.)? Can it ensure data movement at scale?
Asking these questions up front will help you find CDC platforms that meet your infrastructure needs, creating a smoother implementation.
Striim: One Platform for CDC, Streaming, and Beyond
Leading enterprises need a unified CDC platform that combines real-time data capture with in-stream processing and reliable, at-scale delivery. Striim is the only platform providing this end-to-end functionality in a single, enterprise-grade solution. With Striim, your organization gets:
An all-in-one platform: Striim consolidates CDC, streaming, delivery, and observability into a single platform. You get faster time to value and lower TCO, while your engineers are freed from the rigors of having to maintain multiple, cobbled-together systems.
Log-based CDC with sub-second latency: Striim’s log-based CDC extracts changes directly from database transaction logs without impacting production systems, supporting high-throughput workloads, and delivering real-time analytics and cloud sync at scale.
Built-in stream processing: Unlike other CDC tools that just capture change data, Striim you’re your users transform, filter, enrich, and join data in motion using SQL-based processing.
Don’t settle for stale data and fractured data workflows. See how the world’s leading enterprises use Striim to power their business with real-time insights.
Sign up for free or book a personalized demo of Striim now.
