Top ETL Tools

Top 10 ETL Tools for Data Integration

Best CDC Tools for 2024: Capture Real-Time Data Changes

April 2, 2024

Is your organization experiencing a constant flow of data that is similar to a river where every edit, update, and deletion is like a wave in the current? Capturing these ripples and understanding the ever-changing landscape is essential for real-time, informed decision-making. This is where change data capture tools emerge as your life rafts, allowing you to navigate and extract valuable insights from the ever-changing stream. 

As we delve into 2024, a multitude of tools vie for your attention. But with so many options, each boasting unique features and functionalities, how do you identify the one that resonates perfectly with your needs? This article dives deeper than just a list, acting as your trusted guide through the complex world of CDC solutions.  

What is Change Data Capture?

Change Data Capture (CDC) is identifying and capturing changes made to data in a database. It enables monitoring and tracking of modifications such as inserts, updates, and deletes, allowing systems to stay synchronized and updated with real-time changes. CDC is commonly used in data integration, replication, and warehousing scenarios, facilitating efficient and timely updates across different applications and ensuring data consistency. 

CDC typically involves: 

  • Assigning timestamps or sequence numbers to changes to maintain an order and track them accurately. 
  • Log-based implementation, where the database transaction log is examined for changes. CDC can also be carried out through the trigger-based approach, where triggers on tables capture changes when they occur. 
  • Propagating the captured changes to other systems or data repositories to ensure consistent and up-to-date information flow across different distributed system components. 

Benefits of Change Data Capture

CDC offers several advantages over traditional data transfer methods, making it valuable for various data management tasks. Here are some key benefits of using CDC: 

  • Real-time Data: Unlike batch processing, which transfers data periodically, CDC captures the modifications as they happen, enabling real-time data movement and analysis. This is crucial for applications that require up-to-date information, such as fraud detection, stock market analysis, and personalized recommendations. However, you can also use CDC to send data in batches. 
  • Reduced Resource Consumption: CDC only transfers the changed data, minimizing the amount of data transfer and processing compared to full data transfers. This translates to lower bandwidth usage, less strain on system resources, and improved overall efficiency. 
  • Faster and more Efficient Data Migration: With the CDC technique, you can experience smoother and faster data migration with minimal downtime by continuously capturing changes. Since the target system is constantly updated with the latest changes, it minimizes the disruption to ongoing operations.  
  • Simplified Application Integration: It allows for easier integration between applications that use different database systems. By capturing changes in a standardized format, CDC enables seamless understanding and utilization of data from other systems. 

Which are the Top 5 CDC Tools?

Here are some top CDC tools listed below that you can use to seamlessly replicate your data in real-time:

Airbyte

Airbyte

Airbyte is a data integration platform that focuses on replicating data from various sources to data warehouses, lakes, and databases. It supports log-based (CDC), where these logs store the record of changes that have occurred in the database. To assist log-based CDC, Airbyte uses Debezium as an embedded library to capture and monitor changes constantly from your databases. This includes capturing various operations like INSERT, UPDATE, and DELETE.  

Key features of Airbyte include:

  • Although Airbyte provides 350+ pre-built connectors, if your sources are not supported by these pre-built connectors, Airbyte’s Connector Development Kit (CDK) allows you to build custom connectors. 
  • Airbyte supports both homogeneous and heterogeneous migrations. This allows you to replicate data between the same sources (e.g., MySQL to MySQL) and with different database engines (e.g., MySQL to PostgreSQL). 
  • Airbyte’s PyAirbyte is an open-source Python library that allows you to work with the connectors Airbyte provides. This is effective for custom data integration and transformation requirements using Python programming.

Pricing 

Airbyte offers three pricing versions—Airbte Cloud, Self-managed and Powered by Airbyte. The Open-source version is freely available for all and maintained by Airbyte’s community available in the Self-managed plan. The Cloud works on a pay-as-you-go approach, allowing you to only pay for the services you use. The Powered by Airbyte enables you to add hundreds of integrations to your existing product instantly. The pricing of this model depends on the syncing frequency you select.

Debezium 

Debezium

Debezium is an open-source distributed platform designed to capture changes in data. It is built on top of Apache Kafka, a popular streaming platform. Debezium is developed to monitor the transaction logs and capture events representing the modifications to the data. It provides connectors for various database management systems (DBMS) like PostgreSQL, MySQL, and MongoDB. These connectors allow you to capture database changes in real time and stream them to Kafka topics for further processing.

Here’s key aspects of Debezium:

  • If a Debezium source connector generates a change event for a table without an existing target topic, the topic is created during runtime. The change events are subsequently ingested into Kafka.
  • Debezium lets you mask the values of specific columns in a schema. This feature is especially useful when your dataset contains sensitive data. 

Pricing

As Debezium is an open-source platform, it is free of cost for use. 

Striim 

Striim

Striim is a software outlet designed for real-time data integration and streaming analytics. It allows your organization to continuously collect, process, and deliver data from various sources, including databases, applications, and sensors. Striim also facilitates data migration from on-premises databases to cloud environments without downtime and keeps them up-to-date using CDC. 

Here are some features of Striim:

  • Multiple stream sources, windows, and caches can be combined in a single query and chained together in directed graphs, known as data flows. These data flows can be built through the UI or the TQL scripting language. You can easily deploy and scale across a Striim cluster without writing additional code.
  • You can use Striim for OpenAI and parse any type of data from one of Striim’s 100+ streaming sources into the JSONL format. It can be easily uploaded to OpenAI for creating AI models.

Pricing

Striim offers four pricing versions—Striim Developer, Automated Data Streams, Striim Cloud Enterprise, and Striim Cloud Mission Critical. The Striim Developer version is freely available to you. The Automated Data Streams start from $1000 per month. The Strim Cloud Enterprise costs $2000 per month, providing you with more advanced functionalities. Lastly, the Striim Cloud Mission is a customized version, and you can contact the Striim sales team for more details.

AWS Database Migration Service 

AWS Database Migration Service

Managed by AWS, Database Migration Service (DMS) helps you replicate your databases. You can set up CDC to capture changes while you are migrating your data from the source to the target data. Additionally, you can create a task to capture the ongoing changes from the source data. This ensures that any modifications that occur during the migration process are also replicated in the target system. 

Here are the features of AWS DMS:

  • DMS supports a variety of popular database engines, including Oracle, SQL Server, PostgreSQL, MySQL, MongoDB, MariaDB, and others. This allows you to migrate your databases regardless of the platform they are currently on. 
  • AWS offers a serverless option with AWS DWS Serverless. This option automatically provisions, monitors, and scales resources, simplifying the migration process and eliminating the need for manual configuration. It is particularly beneficial for scenarios where diverse database engines are involved. 

Pricing

AWS DMS offers you multiple hourly pricing options. You can contact the AWS team for their pricing details.

GoldenGate (Oracle)

GoldenGate (Oracle)

Oracle GoldenGate is a real-time data integration and replication platform from Oracle Corporation. It facilitates the real-time movement of data between different types of databases and platforms without impacting the performance of the source system. It allows you to capture data changes as they occur and replicate them timely to the target system. 

The features of Oracle GoldenGate include: 

  • GoldenGate offers Stream Analytics, which gives you access to features such as time series, machine learning, geospatial, and real-time analytics. 
  • Along with Oracle repositories, GoldenGate allows you to connect with many non-Oracle databases and data services for data integration. The databases supported by OCI are Microsoft SQL Server, IBM DB2, Teradata, MongoDB, MySQL, PostgreSQL, etc. 

Pricing

OCI offers different pricing versions for different needs, and you can contact their sales team for more details. 

Wrapping Up!

The array of CDC tools available listed above empowers your organization to manage and analyze data effectively. From surveillance to prevention, these tools play a crucial role in fostering data-driven decision-making. Choosing the right CDC tool depends on your specific needs and priorities. Consider the features mentioned above and evaluate options to find the best fit for your data integration. 

What should you do next?

Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey:

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TL;DR

The most prominent ETL and ELT tools to transfer data from include:

  • Airbyte
  • Fivetran
  • Stitch
  • Matillion
  • These ETL and ELT tools help in extracting data from and other sources (APIs, databases, and more), transforming it efficiently, and loading it into a database, data warehouse or data lake, enhancing data management capabilities. Airbyte distinguishes itself by offering both a self-hosted open-source platform and a Cloud one..

    What is ETL?

    ETL (Extract, Transform, Load) is a process used to extract data from one or more data sources, transform the data to fit a desired format or structure, and then load the transformed data into a target database or data warehouse. ETL is typically used for batch processing and is most commonly associated with traditional data warehouses.

    What is ELT?

    More recently, ETL has been replaced by ELT (Extract, Load, Transform). ELT Tool is a variation of ETL one that automatically pulls data from even more heterogeneous data sources, loads that data into the target data repository - databases, data warehouses or data lakes - and then performs data transformations at the destination level. ELT provides significant benefits over ETL, such as:

    • Faster processing times and loading speed
    • Better scalability at a lower cost
    • Support of more data sources (including Cloud apps), and of unstructured data
    • Ability to have no-code data pipelines
    • More flexibility and autonomy for data analysts with lower maintenance
    • Better data integrity and reliability, easier identification of data inconsistencies
    • Support of many more automations, including automatic schema change migration

    For simplicity, we will only use ETL as a reference to all data integration tools, ETL and ELT included, to integrate data from .

    How data integration from to a data warehouse can help

    Companies might do ETL for several reasons:

    1. Business intelligence: data may need to be loaded into a data warehouse for analysis, reporting, and business intelligence purposes.
    2. Data Consolidation: Companies may need to consolidate data with other systems or applications to gain a more comprehensive view of their business operations
    3. Compliance: Certain industries may have specific data retention or compliance requirements, which may necessitate extracting data for archiving purposes.

    Overall, ETL from allows companies to leverage the data for a wide range of business purposes, from integration and analytics to compliance and performance optimization.

    Criterias to select the right ETL solution for you

    As a company, you don't want to use one separate data integration tool for every data source you want to pull data from. So you need to have a clear integration strategy and some well-defined evaluation criteria to choose your ETL solution.

    Here is our recommendation for the criteria to consider:

    • Connector need coverage: does the ETL tool extract data from all the multiple systems you need, should it be any cloud app or Rest API, relational databases or noSQL databases, csv files, etc.? Does it support the destinations you need to export data to - data warehouses, databases, or data lakes?
    • Connector extensibility: for all those connectors, are you able to edit them easily in order to add a potentially missing endpoint, or to fix an issue on it if needed?
    • Ability to build new connectors: all data integration solutions support a limited number of data sources.
    • Support of change data capture: this is especially important for your databases.
    • Data integration features and automations: including schema change migration, re-syncing of historical data when needed, scheduling feature
    • Efficiency: how easy is the user interface (including graphical interface, API, and CLI if you need them)?
    • Integration with the stack: do they integrate well with the other tools you might need - dbt, Airflow, Dagster, Prefect, etc. - ? 
    • Data transformation: Do they enable to easily transform data, and even support complex data transformations? Possibly through an integration with dbt
    • Level of support and high availability: how responsive and helpful the support is, what are the average % successful syncs for the connectors you need. The whole point of using ETL solutions is to give back time to your data team.
    • Data reliability and scalability: do they have recognizable brands using them? It also shows how scalable and reliable they might be for high-volume data replication.
    • Security and trust: there is nothing worse than a data leak for your company, the fine can be astronomical, but the trust broken with your customers can even have more impact. So checking the level of certification (SOC2, ISO) of the tools is paramount. You might want to expand to Europe, so you would need them to be GDPR-compliant too.

    Top ETL tools

    Here are the top ETL tools based on their popularity and the criteria listed above:

    1. Airbyte

    Airbyte is the leading open-source ELT platform, created in July 2020. Airbyte offers the largest catalog of data connectors—350 and growing—and has 40,000 data engineers using it to transfer data, syncing several PBs per month, as of June 2023. Major users include brands such as Siemens, Calendly, Angellist, and more. Airbyte integrates with dbt for its data transformation, and Airflow/Prefect/Dagster for orchestration. It is also known for its easy-to-use user interface, and has an API and Terraform Provider available.

    What's unique about Airbyte?

    Their ambition is to commoditize data integration by addressing the long tail of connectors through their growing contributor community. All Airbyte connectors are open-source which makes them very easy to edit. Airbyte also provides a Connector Development Kit to build new connectors from scratch in less than 30 minutes, and a no-code connector builder UI that lets you build one in less than 10 minutes without help from any technical person or any local development environment required.. 

    Airbyte also provides stream-level control and visibility. If a sync fails because of a stream, you can relaunch that stream only. This gives you great visibility and control over your data. 

    Data professionals can either deploy and self-host Airbyte Open Source, or leverage the cloud-hosted solution Airbyte Cloud where the new pricing model distinguishes databases from APIs and files. Airbyte offers a 99% SLA on Generally Available data pipelines tools, and a 99.9% SLA on the platform.

    2. Fivetran

    Fivetran is a closed-source, managed ELT service that was created in 2012. Fivetran has about 300 data connectors and over 5,000 customers.

    Fivetran offers some ability to edit current connectors and create new ones with Fivetran Functions, but doesn't offer as much flexibility as an open-source tool would.

    What's unique about Fivetran? 

    Being the first ELT solution in the market, they are considered a proven and reliable choice. However, Fivetran charges on monthly active rows (in other words, the number of rows that have been edited or added in a given month), and are often considered very expensive.

    Here are more critical insights on the key differentiations between Airbyte and Fivetran

    3. Stitch Data

    Stitch is a cloud-based platform for ETL that was initially built on top of the open-source ETL tool Singer.io. More than 3,000 companies use it.

    Stitch was acquired by Talend, which was acquired by the private equity firm Thoma Bravo, and then by Qlik. These successive acquisitions decreased market interest in the Singer.io open-source community, making most of their open-source data connectors obsolete. Only their top 30 connectors continue to be  maintained by the open-source community.

    What's unique about Stitch? 

    Given the lack of quality and reliability in their connectors, and poor support, Stitch has adopted a low-cost approach.

    Here are more insights on the differentiations between Airbyte and Stitch, and between Fivetran and Stitch.

    Other potential services

    Matillion

    Matillion is a self-hosted ELT solution, created in 2011. It supports about 100 connectors and provides all extract, load and transform features. Matillion is used by 500+ companies across 40 countries.

    What's unique about Matillion? 

    Being self-hosted means that Matillion ensures your data doesn’t leave your infrastructure and stays on premise. However, you might have to pay for several Matillion instances if you’re multi-cloud. Also, Matillion has verticalized its offer from offering all ELT and more. So Matillion doesn't integrate with other tools such as dbt, Airflow, and more.

    Here are more insights on the differentiations between Airbyte and Matillion.

    Airflow

    Apache Airflow is an open-source workflow management tool. Airflow is not an ETL solution but you can use Airflow operators for data integration jobs. Airflow started in 2014 at Airbnb as a solution to manage the company's workflows. Airflow allows you to author, schedule and monitor workflows as DAG (directed acyclic graphs) written in Python.

    What's unique about Airflow? 

    Airflow requires you to build data pipelines on top of its orchestration tool. You can leverage Airbyte for the data pipelines and orchestrate them with Airflow, significantly lowering the burden on your data engineering team.

    Here are more insights on the differentiations between Airbyte and Airflow.

    Talend

    Talend is a data integration platform that offers a comprehensive solution for data integration, data management, data quality, and data governance.

    What’s unique with Talend?

    What sets Talend apart is its open-source architecture with Talend Open Studio, which allows for easy customization and integration with other systems and platforms. However, Talend is not an easy solution to implement and requires a lot of hand-holding, as it is an Enterprise product. Talend doesn't offer any self-serve option.

    Pentaho

    Pentaho is an ETL and business analytics software that offers a comprehensive platform for data integration, data mining, and business intelligence. It offers ETL, and not ELT and its benefits.

    What is unique about Pentaho? 

    What sets Pentaho data integration apart is its original open-source architecture, which allows for easy customization and integration with other systems and platforms. Additionally, Pentaho provides advanced data analytics and reporting tools, including machine learning and predictive analytics capabilities, to help businesses gain insights and make data-driven decisions. 

    However, Pentaho is also an Enterprise product, so hard to implement without any self-serve option.

    Informatica PowerCenter

    Informatica PowerCenter is an ETL tool that supported data profiling, in addition to data cleansing and data transformation processes. It was also implemented in their customers' infrastructure, and is also an Enterprise product, so hard to implement without any self-serve option.

    Microsoft SQL Server Integration Services (SSIS)

    MS SQL Server Integration Services is the Microsoft alternative from within their Microsoft infrastructure. It offers ETL, and not ELT and its benefits.

    Singer

    Singer is also worth mentioning as the first open-source JSON-based ETL framework.  It was introduced in 2017 by Stitch (which was acquired by Talend in 2018) as a way to offer extendibility to the connectors they had pre-built. Talend has unfortunately stopped investing in Singer’s community and providing maintenance for the Singer’s taps and targets, which are increasingly outdated, as mentioned above.

    Rivery

    Rivery is another cloud-based ELT solution. Founded in 2018, it presents a verticalized solution by providing built-in data transformation, orchestration and activation capabilities. Rivery offers 150+ connectors, so a lot less than Airbyte. Its pricing approach is usage-based with Rivery pricing unit that are a proxy for platform usage. The pricing unit depends on the connectors you sync from, which makes it hard to estimate. 

    HevoData

    HevoData is another cloud-based ELT solution. Even if it was founded in 2017, it only supports 150 integrations, so a lot less than Airbyte. HevoData provides built-in data transformation capabilities, allowing users to apply transformations, mappings, and enrichments to the data before it reaches the destination. Hevo also provides data activation capabilities by syncing data back to the APIs. 

    Meltano

    Meltano is an open-source orchestrator dedicated to data integration, spined off from Gitlab on top of Singer’s taps and targets. Since 2019, they have been iterating on several approaches. Meltano distinguishes itself with its focus on DataOps and the CLI interface. They offer a SDK to build connectors, but it requires engineering skills and more time to build than Airbyte’s CDK. Meltano doesn’t invest in maintaining the connectors and leave it to the Singer community, and thus doesn’t provide support package with any SLA. 

    All those ETL tools are not specific to , you might also find some other specific data loader for data. But you will most likely not want to be loading data from only in your data stores.

    Which data can you extract from ?

    How to start pulling data in minutes from

    If you decide to test Airbyte, you can start analyzing your data within minutes in three easy steps:

    Step 1: Set up as a source connector

    Step 2: Set up a destination for your extracted data

    Choose from one of 50+ destinations where you want to import data from your source. This can be a cloud data warehouse, data lake, database, cloud storage, or any other supported Airbyte destination.

    Step 3: Configure the data pipeline in Airbyte

    Once you've set up both the source and destination, you need to configure the connection. This includes selecting the data you want to extract - streams and columns, all are selected by default -, the sync frequency, where in the destination you want that data to be loaded, among other options.

    And that's it! It is the same process between Airbyte Open Source that you can deploy within 5 minutes, or Airbyte Cloud which you can try here, free for 14-days.

    Conclusion

    This article outlined the criteria that you should consider when choosing a data integration solution for ETL/ELT. Based on your requirements, you can select from any of the top 10 ETL/ELT tools listed above. We hope this article helped you understand why you should consider doing ETL and how to best do it.

    What should you do next?

    Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey:

    flag icon
    Easily address your data movement needs with Airbyte Cloud
    Take the first step towards extensible data movement infrastructure that will give a ton of time back to your data team. 
    Get started with Airbyte for free
    high five icon
    Talk to a data infrastructure expert
    Get a free consultation with an Airbyte expert to significantly improve your data movement infrastructure. 
    Talk to sales
    stars sparkling
    Improve your data infrastructure knowledge
    Subscribe to our monthly newsletter and get the community’s new enlightening content along with Airbyte’s progress in their mission to solve data integration once and for all.
    Subscribe to newsletter

    Build powerful data pipelines seamlessly with Airbyte

    Get to know why Airbyte is the best CDC Tools

    Sync data from CDC Tools to 300+ other data platforms using Airbyte

    Try a 14-day free trial
    No card required.

    Frequently Asked Questions

    What is ETL?

    ETL, an acronym for Extract, Transform, Load, is a vital data integration process. It involves extracting data from diverse sources, transforming it into a usable format, and loading it into a database, data warehouse or data lake. This process enables meaningful data analysis, enhancing business intelligence.

    What is ?

    What data can you extract from ?

    How do I transfer data from ?

    This can be done by building a data pipeline manually, usually a Python script (you can leverage a tool as Apache Airflow for this). This process can take more than a full week of development. Or it can be done in minutes on Airbyte in three easy steps: set it up as a source, choose a destination among 50 available off the shelf, and define which data you want to transfer and how frequently.

    What are top ETL tools to extract data from ?

    The most prominent ETL tools to extract data include: Airbyte, Fivetran, StitchData, Matillion, and Talend Data Integration. These ETL and ELT tools help in extracting data from various sources (APIs, databases, and more), transforming it efficiently, and loading it into a database, data warehouse or data lake, enhancing data management capabilities.

    What is ELT?

    ELT, standing for Extract, Load, Transform, is a modern take on the traditional ETL data integration process. In ELT, data is first extracted from various sources, loaded directly into a data warehouse, and then transformed. This approach enhances data processing speed, analytical flexibility and autonomy.

    Difference between ETL and ELT?

    ETL and ELT are critical data integration strategies with key differences. ETL (Extract, Transform, Load) transforms data before loading, ideal for structured data. In contrast, ELT (Extract, Load, Transform) loads data before transformation, perfect for processing large, diverse data sets in modern data warehouses. ELT is becoming the new standard as it offers a lot more flexibility and autonomy to data analysts.