Top ETL Tools

Top 10 ETL Tools for Data Integration

Top 5 Integrate.io Alternatives 2024

April 16, 2024

Efficient data integration is the foundation of a successful business as it helps unlock valuable insights, discover patterns, and perform robust data analytics. A number of platforms like  Integrate.io have been developed to cater to your integration needs. However, in this growing corporate landscape, the presence of one tool is not enough. Having an understanding of different platforms that offer multiple functionalities is highly preferable. 

This article will give you an overview of the Integrate.io platform, detailing its key features. You will also review the top five Integrate.io alternatives in 2024.

Integrate.io Overview

Integrate.io is a cloud-based platform that allows you to integrate, prepare, and process data for analytics. It supports different integration approaches like ETL and Reverse ETL to efficiently transfer data from one system to another. To facilitate data integration and establish instant connections with popular data sources, the platform is equipped with more than 150 pre-built connectors.

Some of the primary features of Integrate.io include:

  • Since Integrate.io can run on both private and public clouds, it offers flexibility in deployment options. This allows you to choose environments that best suit your needs.
  • It is equipped with CDC capabilities, which quickly capture changes made in your source file and replicate them into the target system. You can easily keep track of the changes made to your datasets and ensure data reliability.
  • Integrate.io adheres to industry standards to safeguard your data. It offers SSL/TLS encryption, firewall-based access control, field-level encryption, and SOC 2 compliance. 

Top 5 Integrate.io Alternatives

Let's look at the top five integrate.io alternatives you can use for data integration.

Airbyte

Airbyte Landing Page

Used by over 40,000 engineers, Airbyte is a popular data integration platform that simplifies the process of connecting data sources to target systems. It uses the ELT approach to integrate data from databases, applications, and APIs into data lakes, warehouses, and other repositories. 

Some of the unique features of Airbyte are:

  • Regarding data security, Airbyte keeps your data safe by encrypting it when it's migrating from source to destination. It has strong security measures, such as audit logging, access controls, encryption, and authentication mechanisms to ensure data integrity and protection.
  • Airbte also supports the Change Data Capture feature, which allows you to identify and capture changes made in the source file to replicate in the destination dataset. This process helps you quickly track changes made to your dataset and manage your data efficiently.
  • With Airbyte, you can leverage several options to monitor your data pipelines. One of the options includes integration with Datadog, which enables you to analyze and monitor your data pipelines within Datadog's dashboards without incurring extra costs.

Pricing

Airbyte offers a transparent and scalable pricing plan in three versions—Airbyte Self-Managed, Airbyte Cloud, and Powered by Airbyte. The first version is accessible to everyone and is ideal for handling small data volumes. The Airbyte Cloud version is a pay-as-you-go model that enables you to use Airbyte’s infrastructure without the hassle of managing servers. In the Powered by Airbyte plan, you can pay based on the syncing frequency duration used while synchronizing your data into the product.

Advantages of Airbyte over Integrate.io

  • Compared to Integrate.io, Airbyte offers double the number of connectors. With its wide variety of more than 350 pre-built connectors, you can enhance your data pipeline tasks. This includes 300+ data sources and over 50 destinations to integrate your data from diverse sources. Additionally, you can request the Airbyte team to provide a new connector to fulfill your integration needs.
  • Being an open-source platform, Airbyte has a vibrant community of data practitioners (800+ contributors) and developers.
  • One of the main features that sets Airbyte apart from Integrate.io is its customizability of connectors. Airbyte allows you to build no-code/low-code custom connectors using the Connector Development Kit within minutes.
  • Airbyte is a clear preference over Integrate.io when it comes to managing data pipelines, as it provides three ways to handle them—UI, Terraform provider, and API. The UI option allows you to build data pipelines without any programming skills. However, if you want to control your data operations programmatically, then API and Terraform Provider would be suitable options.

Skyvia 

Launched in 2014, Skyvia is an integration platform that supports ETL, ELT, and Reverse ETL approaches to transfer data from source to your preferred destination. Due to these capabilities, Skyvia can manage complex operations like data splitting, conversions, and lookups, making the integration process seamless. Along with integration capabilities, Skyvia allows you to replicate incremental changes from your source file into the target system, thus ensuring data consistency across all systems.

 Some of the unique features of Skyvia include:

  • Skyvia possesses robust backup and restore functionality for cloud applications to keep your datasets safe. It enables you to perform scheduled or manual backups so your data is not lost during replication. 
  • With Skyvia, you get an extensive collection of 160+ pre-built connectors for streamlining integration across your desired platforms. However, if you cannot find your preferred connector, you can request a new data connector on Skyvia to automate your workflows.
  • You can create a synchronization package in Skyvia that allows you to perform bi-directional data synchronization between cloud applications and relational databases. Skyvia also enables you to synchronize data with different structures, preserves all data relations, and provides powerful mapping settings for configuring the entire operation. 

Pricing

Based on your business needs and the data you utilize, Skyvia offers multiple pricing plans—Free, Basic, Standard, and Professional. The Free plan is used for basic integration of small data volumes and can be used by everyone. The Basic version offers the ELT tool to integrate data based on the number of records per month. The Standard plan is recommended if you want access to ETL and ELT approaches. However, the Professional plan would be suitable if you aim to build robust and scalable data pipelines for any scenario.

Informatica 

Informatica is a data integration and management platform tailored to migrate your data efficiently. You can quickly extract your data from diverse sources, transform it according to your enterprise needs, and load it into a data warehouse. This allows you to organize and manage your datasets and analyze metadata from its different repositories. 

Some of the unique features of Informatica are:

  • With Informatica, you can leverage several data transformation functions such as aggregation, filtering, masking, and many more. Moreover, it allows you to process your data in real time and batch to ensure timely data processing for diverse business needs.
  • Informatica possesses artificial intelligence features like CLAIRE AI, which you can use to automate your data management tasks. This reduces the complexity of managing large datasets and saves time.
  • It also enhances the data quality of datasets using profiling features. You can assess your data structure and quality, along with spotting anomalies, if any. 

Pricing

Informatica offers a consumption-based pricing model where you have to pay only for the amount of data you consume. For this purpose, the Informatica Processing Unit (IPU) is used to estimate the capacity of your integration requirements in advance. Besides this, Informatica also comes with a free version to fulfill your cloud data integration needs, where you can perform basic transformations. Their paid versions are undisclosed, and if you want to know more about their pricing, you can connect with their sales team.

Matillion

Created in 2011, Matillion is a cloud-based ETL solution that allows you to seamlessly extract, transform, and load data to your desired data warehouse or any destination. You can also integrate your data from different sources using its library of 150+ pre-built connectors, thus simplifying data connection between the source files and the target system. 

Some of the unique features of Matillion include:

  • Matillion possesses data transformation capabilities such as profiling, cleansing, and enrichment to ensure accurate data visualization.
  • With Matillion, you can leverage data security features such as multi-factor authentication, role-based access control, and audit logs to ensure data integrity and confidentiality. In addition, it also provides you with Single Sign-on functionality to log in smoothly without compromising security.

Pricing

Matillion provides a flexible pay-as-you-go pricing model to scale your enterprise needs. It offers three versions to fulfill your integration needs—Basic, Advanced, and Enterprise. The Basic plan hosts limited users and is suitable for transforming and orchestrating pipelines using built-in connectors. The Advanced version has all the Basic plan features and is accessible to unlimited users. The Enterprise version includes all the Basic and Advanced plan features along with additional capabilities such as CDC pipelines and hybrid cloud deployment.

Hevo Data

Created in 2017, Hevo Data is a powerful cloud-native data integration and replication platform. It allows you to extract data from more than 150 data sources, including databases and SaaS applications, and load it to 15+ destinations using its library of pre-built connectors. This helps you to automate your integration process and leverage this unified data to perform analytics and visualization.

Some of the unique features of Hevo Data are:

  • Hevo employs the CDC feature so that you can easily track and capture data changes from your source files and replicate them to your destinations.
  • You can quickly set up a data pipeline within minutes in a four-step process using Hevo. These include configuring the source, selecting data tables, setting up the destination, and finalizing the settings. 
  • With Hevo, you can safeguard your data as it adheres to the best security practices such as SOC 2, GDPR, and HIPAA to maintain data confidentiality.

Pricing

The pricing plan Hevo offers is transparent and comes in three versions—Free, Starter, and Professional. The Free version is accessible to everyone and is tailored to handle small data volumes. You can utilize its Starter plan to move a limited amount of data from databases using its 150 connectors library. However, if you are dealing with excessive data, you should use the Standard plan as it offers better data control and management.

Final Word

While integrate.io is sufficient to manage integration needs, it is always better to have knowledge of other platforms with better features. This article has given you a quick glance at the different data integration platforms you can utilize to expedite your data integration and management processes. 

However, if you want a one-stop solution with advanced features to fulfill your data integration and replication needs, then Airbyte is the perfect choice for you. Sign up on the Airbyte platform today to uncover its amazing features and functionalities for efficient data analytics.

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 Integrate.io Alternatives

    Sync data from Integrate.io Alternatives 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.