Top ETL Tools

Top 10 ETL Tools for Data Integration

Top 4 Data Governance Tools for Compliance & Management

April 1, 2024

Data is present everywhere in the form of records such as sales, marketing, transactions, reports, and surveys. These data are gathered from multiple sources and put into a centralized repository for improved data analysis. However, before analyzing information, it is crucial to ascertain the accuracy and consistency of datasets as it can lead to financial risks, opportunity loss, and legal problems. This is where the role of data governance takes center stage. It ensures the dataset is authentic, secure, and meets the industry standards and policies.

In this article, you will go through the concept of data governance and its major benefits. You will also learn about the top four data governance tools that you can use for maintaining data integrity and security.

What is Data Governance?

Data governance is the comprehensive set of policies, practices, and tools for overseeing the data assets of an organization at every phase of its lifecycle. It helps you align data requirements with your business goals, enhancing data management, quality, visibility, security, and compliance across the entire organization. By implementing an effective data governance strategy, you can swiftly access data for data-backed decision-making, safeguard it from unauthorized access, and ensure regulatory compliance.

Importance of Data Governance

Data management is vital, but it can be vulnerable to breaches and leaks. However, data governance helps address these issues by establishing clear roles, procedures, and standards for efficient data handling. This minimizes risk and ensures data security. Some of the key benefits of implementing data governance features include:

  • Improve Data Accuracy: Data governance sets guidelines and procedures that ensure that information is accurate, comprehensive, and consistent. This ascertains fewer errors, higher-quality data, and more confidence in data-based decisions.
  • Ensure  Regulatory Compliance: Implementing data governance will enable you to adhere to legal standards such as the California Consumer Privacy Act (CCPA) and the General Data Protection Regulation (GDPR). Incorporating these compliances will allow you to gain control over your data and possess the right to access, modify, or delete the data.
  • Increased Operational Efficiency: Effective data governance establishes a single source of truth by eliminating data silos. This results in higher productivity, lower expenses, and enhanced security management across the dataset.

Top 4 Data Governance Tools 

Here are the top four data governance tools that you can employ for effective data security and management:

Collibra

Collibra

Collibra is an enterprise-focused data governance platform that encourages data stewardship and offers automated solutions for governance and management. As an integral part of the Data Intelligence Cloud platform, Collibra Data Governance seeks to help you provide your end users with reliable data. Their governance solution can assist you in standardizing regulatory processes and workflows, establishing a shared language for datasets, and facilitating the collection and analysis of relevant data.

Here are some of the key benefits of using Collibra:

  • Data Security: With Collibra, you can securely perform data profiling and quality analysis on your organization's edge server. Its security features ensure that your data never leaves the system and is managed and monitored accordingly. For instance, you can employ SSO to control user access to your dataset. 
  • Data Stewardship: You can effectively organize your day-to-day tasks by using the Collibra Data Stewardship. It allows you to track and maintain your own space in the company's data governance ecosystem. This space gives you an overview of the responsibilities inside the data governance structure.
  • Data Privacy: The data privacy feature enables you to recognize and protect sensitive personal and business-related information using automatic data classification. 
  • Industry Certifications: Collibra provides a managed solution to comply with privacy regulations and adheres to several data protection laws, such as CCPA and GDPR. This gives you the authority to protect your data from external threats and vulnerabilities.

Axon Data Governance (Informatica)

Informatica

Axon Data Governance, Informatica’s product suite, is a powerful data governance tool that enables your organization to deliver reliable data. It leverages AI and machine learning capabilities to automate data discovery, quality, and consistency. Beyond these features, it also allows you to identify gaps in datasets, establish connections between data elements, and discover shared data.

Here are some of the key benefits of using Axon Data Governance:

  • Data Lineage: Informatica allows you to leverage automated data lineage tracing. It monitors data flow from high-level system views to small-scale column-level details. This comprehensive approach enables you to perform a thorough analysis.
  • Data Stewardship: Axon data governance facilitates data stewardship by designating specific responsibilities to data stewards, expediting the process of resolving data issues, and managing data quality.
  • Data Democratization: To share and analyze data across the organization, you can create pre-approved sets of governed data that are accessible to everyone.
  • Compliance Audit Readiness: It enables you to gain control over your data by adhering to regulations, such as HIPAA, CCPA, GDPR, and BCBS 239.

Talend Data Fabric

Talend Data Fabric

Talend Data Fabric is a robust platform that provides data quality, management, and governance solutions. It employs machine learning capabilities to enrich data profiling by identifying quality issues, exploring hidden patterns, and spotting anomalies in the dataset. Beyond these capabilities, it also empowers you to organize, transform, and synchronize data, thus maintaining data integrity.

Here are some of the key benefits of using Talend Data Fabric:

  • Security Certifications: Talend is committed to preserving data confidentiality and integrity by adhering to several industry standards. These compliances include SOC 2 Type 2, HIPAA, Cyber Essentials Plus, GDPR, ISO 27701, and CSA STAR.
  • Data Catalog: With its data cataloging feature, you have a single, safe point of control over your data. You can use it to link, enhance, profile, and organize all of your metadata. With the help of machine learning technologies, you can automatically document up to 80% of the information related to the data and maintain its accuracy.
  • Data Inventory: Its data inventory solution enables you to collaborate with your teammates to identify silos in the data, thus improving the quality of data assets. This makes data quality and curation a systematic process, ensuring data reliability.
  • Data Stewardship: Talend data stewardship promotes collaboration with a team-based approach that simplifies defining goals and tracking data progress across the organization. You can organize, validate, and reconcile the data and assign tasks to others accordingly.

IBM Data Governance

IBM Data Governance

IBM Cloud Pak for Data is a cloud-native platform that facilitates client data management, AI governance, data integration, quality, and privacy actions. The application has AI-driven data discovery, profiling, and categorization features to address data quality issues and ensure accuracy. Apart from resolving quality issues, you can also conduct automated privacy and risk assessments on your dataset to identify and mitigate any potential risks.

Here are some of the key benefits of using IBM Data governance:

  • Data Catalog: In IBM Cloud Pak, a data catalog serves as a consolidated repository for metadata and data assets, making it easier for you to discover, comprehend, and efficiently work on data resources. Cataloging data improves security by providing an extensive overview of data history, usage, and connections.
  • Industry Practices: IBM certifications adhere to FIPS, GDPR, and HIPAA laws. It offers granular control over who has access to or can interact with your data, ensuring absolute confidentiality at all times.
  • Data Security: It provides robust security features such as encryption, access controls, and data masking to safeguard datasets.
  • Flexible Deployment: IBM Cloud Pak for Data can be deployed on-premise, in a cloud, or a hybrid environment according to your business needs to protect sensitive data from unauthorized access.

Optimizing Data Governance Solutions With Airbyte

Airbyte

Before incorporating security features, it is essential to integrate data from multiple sources like databases, flat files, and SaaS applications into a data warehouse. This is where Airbyte comes helps you streamline the process of centralizing data. It follows a modern ELT approach that allows you to seamlessly collect data from disparate sources and load it into a centralized repository. 

You can leverage its extensive library of 350+ pre-built connectors to automate data pipelines within minutes. In addition, if you are not able to find a connector of your choice, you can build a custom connector using CDK or request a new one on its platform.

Airbyte is a reliable platform that facilitates centralized data transfer, simplifies data management, and ensures data quality and integrity across diverse sources and destinations. By integrating Airbyte into your data governance frameworks, you can automate replication processes, streamline integration, and keep a unified view of all of your data assets. This allows you to gain greater visibility and control over your datasets.

Here are some of the key benefits of using Airbyte:

  • Data Security: Airbyte employs encryption methods like SSL or HTTPS to safeguard data in transit and at rest. It also provides access controls and authentication mechanisms to ensure that only authorized users can access data, thereby enhancing overall data governance. 
  • Security Certifications: Airbyte Cloud's ISO 27001 and SOC 2 Type II certifications indicate its dedication to best security practices. In addition, AES-256-bit encryption is also used to encrypt customer metadata at rest, while TLS (Transport Layer Security) is used to encrypt data in transit.
  • Documentation and Logging: Airbyte maintains a record of all platform changes, offering an audit trail for compliance and historical analysis. This helps provide data authenticity and traceability.

Final Word

This article has comprehensively covered data governance and highlighted its key benefits. You also reviewed the top four data governance tools for improved security and compliance. Each tool has been designed to provide different security features and adhere to multiple data privacy rules. You can employ them according to your business needs, as they are designed to ensure data integrity and confidentiality.

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 Data Governance Tools

Sync data from Data Governance Tools to 300+ other data platforms using Airbyte

Try a 14-day free trial
No card required.

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 Data Governance Tools

    Sync data from Data Governance 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.