Top ETL Tools

Top 10 ETL Tools for Data Integration

Top 4 Panoply Competitors & Alternatives 2024

April 16, 2024

In the field of modern data management, businesses are increasingly seeking alternatives to streamline their data integration operations. Panoply offers all-in-one solutions for data management and analytics, but exploring its competitors can provide valuable insights into alternative platforms with their unique features. 

This article explores Panoply alternatives, providing a keen understanding into competitor data management platforms. By examining the features and functionalities of other platforms, you can make informed decisions regarding your management needs.

Panoply Overview

Panoply is a comprehensive data management platform that streamlines the process of data integration and analytics. It enables you to centralize your disparate data sources, automate ETL processes, and gain actionable insights through powerful analytics tools. With its user-friendly interface and scalable architecture, Panoply caters to the needs of both small and large business enterprises. With this tool, you can get a competitive edge in the big data industry.

Here are some key features:

  • It supports real-time data updates, enabling you to instantaneously ingest and analyze streaming data sources, facilitating timely decision-making.
  • Panoply's Workbench empowers you to visualize query results directly within the platform. This eliminates the need for exporting data and switching between applications, allowing for seamless exploration and analysis.

Top Panoply Competitors & Alternatives in 2024

While Panoply offers a robust solution, it's essential to acknowledge the existence of its competitors. If you are seeking different approaches to data integration, management, and analytics, you can go with one of Panoply’s alternatives.  Let’s take a look at them:

Airbyte

Airbyte is one of the leading data integration and replication platforms that empower you to migrate data seamlessly. It acts as a bridge, allowing you to connect and integrate datasets from a wide range of sources, such as SaaS applications, databases, and flat files. Through Airbyte’s data pipelines, you can efficiently collect, synchronize, and load large datasets into data lakes, warehouses, or other databases.

Key features include:

  • Airbyte offers a massive library of over 350+ pre-built connectors, allowing you to connect to various sources. But if you need a specific connector that you cannot find on the platform, create a custom one in minutes. You can use Airbyte’s Connector Development Kit (CDK), which helps you build a no-code or low-code connector quickly.
  • Airbyte's CDC feature replicates only the incremental changes from your source systems, ensuring your destination databases and warehouses are continuously updated with the latest data.
  • Airbyte's integration with Datadog makes the process of extracting valuable insights from your data pipelines quick and easy. You can visualize and analyze data directly within Datadog's dashboards, saving your time and resources.
  • Manage and automate your Airbyte deployments and configurations programmatically with the Airbyte Cloud and the open-source edition, which seamlessly integrates with your existing infrastructure and workflows.

Airbyte Advantages over Panoply

While Panoply is a comprehensive data management platform, Airbyte presents several distinct advantages, particularly if you are seeking more flexibility, control, and cost-effectiveness.

  • Compared to Panoply's limited selection of 205 connectors, Airbyte has a vast and rapidly growing library of over 350+ pre-built connectors.
  • Airbyte empowers users with limited programming knowledge and technical expertise to build custom connectors. This way, the platform caters to unique data sources which Panoply does not support. 
  • You can seamlessly integrate Airbyte with various stack tools like Airflow, Prefect, Dagster, and dbt. Compared to Panoply's potentially limited integration options, Airbyte has enhanced compatibility with existing data ecosystems.
  • Airbyte has a vibrant community of users and developers. It also offers multiple user interfaces (UI) to cater to different preferences and skill levels. It includes a web UI, a Terraform provider, and a programmatic API. This flexibility empowers you to choose the approach that best suits your needs.

Pricing

Airbyte offers transparent pricing plans with three versions—Airbyte Cloud, Airbyte Self-Managed, and Powered by Airbyte. Airbyte Cloud comes with hassle-free deployment and a pay-as-you-go model for a managed solution. The Self-Managed option is free and provides full control if you want to host and manage your platform yourself. Finally, Powered by Airbyte integrates your data directly within your software product, utilizing tailored pricing based on sync frequency and duration.

Fivetran

Fivetran simplifies data integration by letting you automate the ETL (extract, transform, load) process. It functions as a fully managed data integration platform, acting as a bridge between various data sources and your chosen destination. The platform’s automation eliminates the need for manual coding and data pipeline management, streamlining workflows and freeing up resources for analysis and decision-making. Fivetran further empowers dataset management through its centralized platform, facilitating the control of data connections and transformations from a single location.

Key features include:

  • You can schedule automatic data refreshes to ensure real-time access to your data and eliminate manual intervention. Fivetran also handles automatic retries for failed transfers, guaranteeing seamless data flow.
  • Fivetran identifies and transfers only new or changed data since the last sync, minimizing bandwidth usage and data transfer fees. This is particularly beneficial for large datasets or frequently updated sources.
  • You can cleanse, filter, and manipulate data directly within Fivetran's user-friendly platform. It eliminates the need for separate transformation tools, streamlining data preparation for analysis.
  • Fivetran lets you track the complete journey of your data from source to destination. This transparency simplifies troubleshooting, ensures data integrity, and facilitates compliance with regulations.

Fivetran Advantages over Panoply

  • Compared to Panoply's potentially manual refresh processes, Fivetran automates data synchronization, saving precious time and effort.
  • With Fivetran, you get granular control over data transfer, which is lacking in Panoply.

Pricing

Fivetran adapts to your data needs, offering a unique blend of affordability and scalability. The free plan allows you to experiment with the platform and handle smaller data volumes without any upfront cost. As your data requirements grow, Fivetran transitions with you. Paid plans, categorized as Starter, Standard, and Enterprise, cater to increasingly complex needs by offering higher data volume limits, increased connector access, and advanced security features. This tiered structure means you only pay for the functionalities you require, making Fivetran a cost-effective solution.

Stitch (Talend)

Stitch (Talend) is a data integration platform that automates the movement of data from various sources to your data warehouse or lake. The platform eliminates the need for manual ETL (extract, transform, load) processes, saving you time and resources. Stitch offers pre-built connectors for popular applications and centralizes data management, providing a user-friendly experience for streamlined data integration.

Key features include:

  • Stitch offers seamless integration with Talend Cloud, allowing you to leverage its data preparation and analysis capabilities. This unifies your data journey within the Talend ecosystem, potentially offering additional functionalities and workflow optimization for businesses already utilizing Talend Cloud.
  • It provides advanced error handling and data validation capabilities, helping you identify and address potential issues within your data pipelines. 
  • With Stitch, you can get in-depth data lineage tracking. The platform emphasizes data governance by providing detailed lineage information, compliance with regulations, and enabling easier troubleshooting.

Stitch Advantages over Panoply

  • Unlike manual workflows in Panoply, Stitch prioritizes automation in data integration processes through features like scheduled data refreshes and error handling.

Pricing

Stitch prioritizes cost-effectiveness with its transparent, pay-as-you-go pricing. Tailor your plan based on your data volume with three pricing plans. The Standard plan (5 million to 300 million rows/month) is well-suited for smaller businesses. The Advanced edition (exceeds 100 million rows/month) provides additional features for growing teams, and Premium plan caters to massive datasets. This ensures you only pay for the resources you need, making Stitch a scalable solution for organizations of all sizes.

Matillion

Matillion is a cloud-based platform designed to simplify data integration and management. It allows you to extract data from various sources, transform it for analysis, and load it into a central location. This streamlines the process of gathering and preparing data, making it readily available for insights. Matillion offers features like data cleansing, transformation, and orchestration, empowering you to manage your data pipelines efficiently.

Key features include:

  • Matillion boasts a user-friendly interface that utilizes drag-and-drop functionality. This intuitive interface simplifies data management tasks, making it accessible if you have limited technical expertise.
  • You can connect to a wide range of data sources, including databases, applications, and cloud storage, to gather data from all your relevant systems.
  • Matillion offers multi-cloud support, allowing seamless integration with various cloud providers like Snowflake, AWS, Azure, and Google Cloud. 

Advantages over Panoply

  • Matillion allows you to build tailored connectors for any REST API that returns JSON data, enabling integration with a wide range of sources. Thus, you have specialized or niche connectors compared to the ones found in Panoly.

Pricing

Matillion offers a simple and adaptable pricing model to suit your various data needs. Choose from the Basic, Advanced, or Enterprise editions with different features and functionality. You can purchase capacity upfront for predictable budgeting. This consumption-based pricing ensures you only pay for the credits you use, allowing you to scale your data workflows efficiently and cost-effectively.

Conclusion

The data management ecosystem continues to expand, offering you a multitude of alternatives beyond established platforms like Panoply. Exploring these Panoply competitors allows you to discover solutions that seamlessly integrate with your existing infrastructure.

While everyone has unique needs, some platforms consistently garner attention for their specific strengths. For instance, take Airbyte as one of the Panoply alternatives. Its extensive library of pre-built connectors and no-code/low-code custom connector capabilities empower users of all technical backgrounds to connect to virtually any data source. This promotes flexibility and eliminates dependency on pre-existing integrations. Finally, its user-centric approach and its cost-effectiveness make it one of the best alternatives to Panoply.

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 panoply-alternatives

    Sync data from panoply-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.