Top 12 Change Data Capture (CDC) Tools Simplifying Data 

80% of businesses that don’t currently have a cloud strategy are planning to adopt it in the next five years, and scalable data processing will be at the core of data transformation success. Slow and inaccurate data processing can hinder real-time visibility over operations, limit transaction speeds, and prevent organizations from making data-driven decisions. 

Besides processing speeds, data is continuously changing. So the question is, who can keep up? 60% of organizations are not confident in their data and analytics, while only 10% believe they do a good job of managing and analyzing data. In a world that relies and thrives on data, mastering it is a critical competitive advantage. 

Using CDC (Change Data Capture) tools is one of the best methods to address modern data’s complexities. CDC tools allow organizations to quickly identify the data changes and take the rapid action required to scale their businesses. 

This article will discuss what CDC is, why you need it, and which CDC tools you should consider to help drive your business forward. 

What is Change Data Capture?

Change data capture (CDC) is a process that enables organizations to automatically identify database changes. It provides real-time data movements by capturing and processing data continuously as soon as a database event occurs.

The key purpose of CDC is to ensure data accuracy to capture every data change as it happens. In the context of ETL (extract, transform, load) pipelines, which organizations widely use to transform data to target systems, CDC enables greater accuracy where older versions of ETL could only extract data bulks. Instead of a slow data processing pipeline, CDC integration eliminates the need for bulk updates, preventing system lags and downtime. 

Should you use CDC Tools?

Implementing a CDC process all by yourself is not an easy task, especially as it requires integration of multiple tools into your data architecture. That’s why it is always best to use a CDC tool instead of building a process of your own. 

There are many elements to consider, including equipping your development team with the knowledge and automation tools to monitor CDC. The best CDC tools are compatible with various data sources and data types. We’ll look at a few top-ranking options in the next section. 

Top 12 Change Data Capture tools

1. IBM Infosphere

The IBM Infosphere data integration platform enables data cleansing, transformation, and monitoring. It’s highly scalable and flexible, and its massively parallel processing (MPP) capabilities allow you to manage large volumes of data and scale accordingly.

Pros

  • Simple for both users and managers.
  • Straightforward integrations.
  • Performance is consistent and well-optimized.
  • Provides real-time data migrations that don’t compromise data quality.

Cons

  • You should be familiar with the app server aspects to maximise the platform.
  • No access to proper technotes on the IBM site in case of errors.
  • High price. 

2. Equalum

Equalum is a powerful log-based CDC tool with continuous data integration and real-time ETL streaming capabilities. It provides a fully managed, enterprise-grade CDC streaming solution that offers unlimited scale to increase data volumes, improve performance, and minimize system impact. To keep up with your digital transformation and cloud adoption journey, Equalum ingests data from on-premise to a cloud-based data warehouse for real-time visibility.

Pros

  • Provides an enterprise-class data ingestion platform for collecting, transforming, manipulating, and synchronizing data from multiple sources. 
  • Combines modern data transformation and manipulation with batch and streaming pipelines.
  • Create and deploy data pipelines in minutes.

3. Oracle GoldenGate

Oracle GoldenGate offers CDC and real-time delivery between heterogeneous systems to instantly replicate, transform, and filter transactional data from databases. It leverages CDC data replication from multiple sources to provide real-time analysis. In addition, it can replicate other sources, including Microsoft, IBM DB2, MongoDB, MySQL, and Spark.

Pros

  • Transfers data between databases to enable propagation in real-time.
  • Transforms data as it is transferred from tables in the same or separate databases.

Cons

  • On busy systems, online DDL updates might occasionally result in data mismatch for active-active replication.
  • High memory usage.
  • The system has numerous issues that prevent data dumping in XML or other formats like hdfs.

4. Precisely

Precisely is a leading data integrity company that provides a set of tools for data integrity management, including a CDC tool. It is used in over 100 countries and ensures maximum accuracy and consistency of your data.

Pros

  • Easy to integrate with mainframes and data lakes.
  • Can perform data mining tasks quickly.

Cons

  • Not suitable for data preparation.
  • GUI is not mature enough to establish connectivity with databases.

5. Keboola

Keebola is a cloud-based data platform that can distribute, modify, and integrate critical information quickly and simply. It’s a complete platform for data operations, with over 250 available connections to link data sources and destinations.

Pros

  • Competent data management, which improves analytical efficiency.
  • Customized data sourcing for accurate analysis.
  • Extended tools for business analysis.

Cons

  • Integration with Active Directory is difficult.
  • The pay-as-you-go system is quite expensive after the first five hours.

6. Fivetran

Fivetran is a fully automated data pipeline solution that centralizes data from any source and transports it to any warehouse. Fivetran mainly employs log-based replication and provides CDC as a feature. It can replicate databases, transfer data between on-premises systems and the cloud, and continuously monitor changes in data.

Pros

  • The data source connectors are high-quality and straightforward to use.
  • Running SQL scripts for integration and reports is simple for non-database users.
  • Big data ingestion is user-friendly and configuration-driven.

Cons

  • Data cannot be transformed before being sent to the destination.
  • Only a few destinations are supported as data warehouses.

7. Hevo Data

Hevo Data is a no-code data pipeline that can be used to load data into data warehouses. With Hevo, you can import various data sources, including relational databases, NoSQL databases, SaaS apps, files, and S3 buckets in real-time into any warehouse (e.g. Amazon Redshift, Google BigQuery, Snowflake). Hevo supports over 100 pre-built integrations, each of which is based on a native, niche source API.

Pros

  • Configuration and setup are simple.
  • Possibility of implementing ETL without coding knowledge.
  • Seamless data integration.

Cons

  • The changes from the raw connectors can sometimes be a little confusing and require a deep understanding of the source.
  • Writing transformation scripts is complicated.
  • Sometimes models take too much time to run.

8. Talend

Talend is an enterprise-class open-source data integration platform that incorporates CDC compatibility. As a company it provides multiple solutions, and Open Studio for data integration is its main product. It is free to use under an open-source license and offers three distinct models to support big data technologies.

Pros

  • Can move millions of records quickly and efficiently in a single task run.
  • Provides a good preview of the data counts moving between various systems.
  • Property files allow dynamically changing environmental variables easily.

Cons

  • Does not have the necessary components to perform ML-based deduplication and fuzzy matching.
  • Tier 1 applications are challenging to execute because of their low availability.
  • There are no effective methods for testing the components.

9. StreamSets

The DataOps platform from StreamSets has hybrid architecture and smart data pipelines with built-in data drift detection and handling. Along with collaboration and automation features, it supports the design-deploy-operate lifecycle. StreamSets continuously checks data in-flight to spot changes and predicts downstream difficulties.

Pros

  • Easy to use.
  • Many stages are readily available, including sources, processors, executors, and destinations.
  • Supports streaming and batch pipelines.
  • Key-vault integration for secrets fetching.

Cons

  • The logging process is complicated.
  • No option to create global variables.
  • Sometimes you have to keep information stored throughout the executions.

10. Striim

Striim provides a real-time data integration system that enables streaming analytics and continuous query processing. Striim integrates data from various sources, including events, log files, IoT sensor data, transaction/change data, and real-time correlation across several streams. In addition, the platform includes drag-and-drop dashboard builders and pre-built data pipelines.

Pros

  • Despite your data format, the platform gives you a place to prepare it.
  • When integrating with legacy data sources, you can choose from pre-built adapters and connectors or create your own.
  • Easy installations and upgrades.

Cons

  • The platform’s online interface and real-time dashboard are a little bit clunky.
  • High cost.

11. Qlik 

Qlik is a data-moving tool that provides organizations with immediate data insights. It offers features like data replication, replication, and streaming across numerous sources and targets.

Pros

  • Easy to combine data from numerous sources.
  • Highly scalable and flexible.
  • Log reading capability for multiple sources/targets

Cons

  • Initial setup and configuration can take some effort and time.
  • Requires users to write SQL queries or python code to process data.

12. Arcion

Arcion provides log-based CDC that supports many databases, data warehouses, and other popular technologies. It allows you to record DDLs, DMLs, schema changes, and several other non-DML changes. As a result, no-code CDC pipelines become reliable and straightforward to build and maintain.

Pros

  • Supports managed file transfers.
  • Supports data transformation, integration extraction, and analysis.
  • Metadata management.

Cons

  • No data filtering features.
  • Lack of data quality control.
  • No compliance tracking.

CDC: Simplifying Your Data and Your Decision-making

When choosing a CDC tool, you must ensure that it satisfies all your requirements and is scalable enough to keep up with your present and future business goals. Every tool has a different feature, and it could take some time to decide which one is right for you – but it’s worth the research to benefit from real-time analytics and data capture. 

Equalum is an excellent option for many organizations since it enables real-time streaming ETL for replication scenarios, analytics and BI tools, and application integration to maximize your decision-making flow. You can also find how Equalum can support your organization by booking a free demo.

4 Questions You Should Ask About Change Data Capture (CDC) Tools

Change Data Capture (CDC) describes a set of techniques to capture changes from data sources in real-time. CDC is widely considered the lowest-overhead and most effective way to capture changes asynchronously without any change to the source – a critical requirement for enabling real-time analytics and decision making.

Equalum’s approach to data ingestion is based on the timely identification, capture, and delivery of the changes originally made to enterprise data sources, allowing organizations to quickly acquire analytics data to make actionable business decisions that ultimately result in innovation and time/money saved.

CDC is a well-known methodology, and there are several legacy tools that leverage these techniques. These solutions are a natural starting point for data teams looking to empower their business with real-time insights.

But CDC technologies vary widely in their ability to meet critical business needs. Without proper vetting, buyers may find that legacy CDC tools fall short of delivering on essential business use cases – and don’t scale in an ROI-positive way as an enterprise’s needs evolve beyond a specific replication use case to enterprise-wide adoption. Picking the right CDC vendor and the right CDC tool can help you save time, money, and avoid costly headaches.

How can you ensure that you’re getting the best possible change data capture solution that will meet your current needs, and is also scalable enough to meet your needs down the road? Here are four questions you should ask when choosing a CDC vendor:

1. What can your CDC solution do beyond just data replication?

Most legacy Change Data Capture (CDC) tools are built primarily for data replication (reproducing data “as is” from a source to a target). However, businesses often rely on in-flight transformation to make the data useful for analysis. Transformation – which include aggregation, filtering, joining across multiple data sources, or otherwise modifying data – are essential for businesses looking to extract insights from raw data. While legacy CDC tools may offer limited transformation as an add-on for specific replication use cases, savvy buyers should look for robust, full-scale ETL capabilities for streaming data – which help enterprises harness the full power of data in motion to power better, faster decision-making.

The Equalum difference:

Equalum provides in-flight data transformation capabilities that go well beyond replication, including source data modification, data computations and correlation with other data sources. Our platform uses a zero-coding, UI-based approach with limited to no overhead on data sources.

2. What data sources and targets does your CDC tool support?

CDC tools typically provide out-of-the-box integrations to major legacy and widely adopted enterprise databases, but may offer very limited support for new databases and non-database sources and targets. Data-driven enterprises often need to harness the data in applications, files, APIs, message queues, and more. Data from a broader range of sources means a more complete view of your customers and how your business is performing. Data teams should ensure that a solution for in-flight data supports multiple sources and delivery to all your relevant targets.

The Equalum difference:

Equalum offers seamless integration with legacy, newer database technology, and non-database sources. Equalum’s sources include Oracle, SQL Server, Postgres, SAP, and Salesforce. We deliver to a wide range of targets including Snowflake, Azure, and other data lakes and warehouses.

3. How much coding and expertise does your CDC solution require?

Some leading CDC tools require extensive coding that is time-consuming and inconvenient, and offer no UI whatsoever. Other tools include limited UI, but the overall UI/UX is antiquated and doesn’t offer drag and drop and other features that make it easy to build data pipelines and monitor your data flows. Consider avoiding CDC tools that create extra work for your overburdened data teams, and require hours of coding to setup and maintain.

The Equalum difference:

Equalum’s CDC tool includes drag and drop UI with no coding required. This allows engineers to deploy our tool in minutes, instead of days or weeks, and frees up data teams to focus on other projects.

4. How much is this going to cost me?

The pricing model for legacy CDC tools – which typically involves a per-server or CPU usage-based fee – is a good option for small, isolated scenarios of data replication. With this model, costs can add up quickly when a business looks to leverage the technology across a wider range of applications. Data analysts charged with driving widespread usage of real-time insights should look for solutions that offer a license model designed to enable businesses to scale for enterprise-wide adoption without costs increasing dramatically.

Ultimately, solutions that leverage change data capture technology vary widely in their cost, level of technological sophistication, and their ability to address meaningful challenges for data engineers and company-wide data infrastructure. The most successful enterprises are those that are looking for a scalable, end-to-end CDC solution that will meet the needs of business stakeholders and harness the power of data in motion to empower faster and better decision-making.

Equalum Launches CDC Connect Partner Program

Equalum is making news! With the launch of our new OEM program, CDC Connect, technology partners can now integrate our industry-leading change data capture (CDC) tool on their platform or workflow, and benefit from our cutting-edge CDC capabilities. “Many data integration vendors lack strong CDC, said Kevin Petrie, an analyst with Eckerson Research., “so they might benefit by building Equalum CDC Connect into their offerings.” Read more about it at Tech Target.

Equalum CDC Connect embeds change data capture and streaming

By Sean Michael Kerner

Change data capture platform provider Equalum is looking to change the way that organizations use and integrate its technology into data platforms with the CDC Connect program it unveiled on Tuesday.

It has been a busy year for Equalum. In April the vendor released version 3.0 of its Continuous Data Integration Platform, which includes change data capture (CDC), extract, transform, load, and real-time data streaming capabilities. In August, Equalum raised $14 million to expand its go-to-market and technology efforts.

Until now, Equalum has sold its technology, which is available for on-premises and cloud deployments, as a standalone service that organizations and vendors could use as part of an existing data workflow for business operations or data analytics. The CDC Connect program will enable vendors to integrate Equalum inside an existing data or cloud platform as part of another vendor’s larger data workflow offering.

Equalum competes against a number of vendors that offer CDC capabilities including Fivetran, which acquired CDC vendor HVR in 2021; Arcion, which launched a cloud service in April 2022, Oracle and its GoldenGate software platform; and the open source Debezium technology.

Until now, Equalum has offered high-performance integration of data in bulk and in real time, building on Spark and Apache Kafka capabilities as well as CDC.

Now Equalum wants to address a new opportunity, offering its core CDC technology as a white-label component to other data integration vendors, said Kevin Petrie, an analyst with Eckerson Research. The approach offers a way for Equalum to increase its addressable market in a crowded landscape for data integration tools, he said.

“CDC helps replicate high volumes of transactional data from traditional databases, at low latency and ideally with low impact on production workloads,” Petrie said. “Many data integration vendors lack strong CDC, so they might benefit by building Equalum CDC Connect into their offerings.”

The original idea behind CDC technology was to provide a way for organizations to get data out of one database and into another as it changes. It’s an approach that can be enabled today by a variety of methods.

One of the most common ways for CDC to work is by connecting to a database log to capture changes that can then be replicated out to an external source.

Equalum’s platform uses an approach called binary log parsing, a technology that is able to rapidly read and understand all the changes happening in a database.

Equalum uses event streaming technologies including Apache Kafka to stream data from a source database to a target in real time. Going a step further, Equalum integrates data transformation capabilities so data can be converted into the required format and structure for the target database.

Equalum CEO Guy Eilon said the vendor’s goal is to enable organizations to get data from one location to another in a format that makes the data immediately usable for business operations or data analytics.

Why Equalum wants to embed its technology with CDC Connect

The challenge Equalum’s customers often face is managing multiple data technologies in order to enable a data application for business operations, machine learning or data analytics, Eilon said.

With CDC Connect, Equalum’s technology can be embedded into a larger data platform, so users will never actually see the name Equalum.

Eilon declined to immediately disclose the large data platform vendors that he said plan to use CDC Connect.

“The biggest challenge int he data integration world right now is definitely how to move data in real time from legacy and cloud systems towards a single place so users can get answers in real time,” Eilon said. “That is what Equalum is all about.”

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