Top ETL Tools

Top 10 ETL Tools for Data Integration

Four Best Web Scraping Tools

January 30, 2024

Web scraping has emerged as one of the widely adopted methods by organizations to extract publicly available information in different data formats. The demand for robust web scraping tools has grown incrementally as several businesses are looking to gather data to improve their products and services.

This article will take you through some of the best web scraping tools and help you choose a platform that aligns well with your data requirements. Let’s start by understanding what web scraping tools are.

What are Web Scraping Tools? Why are They Important?

Web scraping, also known as web data harvesting, involves the automated process of extracting data from websites. The method is quite useful when you are dealing with projects requiring data extraction from numerous web pages. 

Web scraping tools have been developed to help you efficiently collect data from different websites. You can collate all of this information in a centralized repository, such as a local database or spreadsheet until you are ready to utilize it.

Using the data, you can conduct market research and competitor analysis. You can also build machine learning models for predictive analysis or use business intelligence tools to create interactive dashboards. These further processes help you visualize and easily disseminate the raw data into formats that are understandable by all your stakeholders.

While web scraping can be done manually, it is best to rely on tools that can automate the process for you. With them, you can rapidly access large volumes of data, saving valuable time. The platform can make HTTP requests to a website’s server, download HTML or XML content, and parse the data to provide you with relevant information.

Take a look at some of the well-known web scraping tools in detail to make an informed decision for your business.

Four Best Web Scraping Tools

While web scraping tools can provide you with a host of features that reduce the burden on your existing data processing capabilities, it is vital that you assess your organization’s data requirements before the selection. Here are some of the best web scraping tools available today!


Image Source: Octoparse

Octoparse is a flexible web scraping tool that is crafted to be suitable for a range of users. Even if you do not have extensive experience in coding, you can utilize Octoparse to handle vast amounts of data effectively. This cloud-based solution offers cloud storage services, making it a valuable tool for accommodating varying workloads while providing you with a web scraping solution.

Key Features:

  • Visual Point-and-Click Interface: With Octoparse’s easy-to-use visual interface, all you have to do is click and select the desired data to initiate the web scraping process.
  • Handling Advanced Technologies: Octoparse is capable of scraping and fetching data from websites that use technologies like JavaScript and Ajax. 
  • Anti-Scraping Mechanism: This web scraping tool effectively deals with CAPTCHA and other anti-scraping mechanisms on websites. 
  • Scheduled Scraping: You can schedule scraping frequencies and duration with Octoparse and set alerts to receive updates on your data.

Pricing: Octoparse provides a free plan to get started. However, it has certain limitations, like the maximum number of tasks, which must be ten only. There is a Standard plan beginning from $75 per month and a Professional plan at $208 per month. You can set up a customized Enterprise plan by getting in touch with their sales team.


Image Source: ScraperAPI

ScraperAPI is a user-friendly web scraping tool designed to crawl through large data volumes. The tool exposes a single API endpoint for you to send GET requests–an HTTP request to obtain data from any source. This GET request has two query string parameters, and ScraperAPI returns the HTML response for your desired URL through an API key. You must remember to add appropriate query parameters at the end of the ScraperAPI URL.

Key Features:

  • JavaScript Rendering: ScraperAPI can work around website data that is protected with JavaScript, thereby simplifying the extraction for you.
  • Geo-located Proxy Rotation: Geo-located rotating proxies allow you to circumvent geographic restrictions on data. With ScraperAPI, you can obtain data even from websites where anti-scraping features are enabled.
  • Specialized Proxy Pools: Proxies are created to streamline the scraping process and ensure that you are not blocked or censored by websites while crawling through their data. With this tool, you get access to specialized pools of proxies that can manage CAPTCHAs and browsers for various scraping types like search engines or social media scraping. 
  • Auto Parsing: ScraperAPI collects and parses JSON data from Amazon, Google Search, and Google Shopping and presents it to you in a structured format.

Pricing: You can choose between three monthly pricing plans: Hobby at $49, Startup at $149, and Business at $299. There is a fourth Enterprise plan that you can customize for your organization.


Image Source: ParseHub

ParseHub is another web scraping tool that allows you to conduct data extraction from websites without coding. Its simple user interface helps you to collect data from multiple online sources. The platform offers a ParseHub expression that functions similar to the regular expressions used in programming languages. You can set a conditional (if) command with ParseHub to filter certain results during the scraping process. This can include instances where you need data for top-rated reviews of a product or scraping specific values from certain web pages. The feature eliminates the need for additional refinement of data after collection, saving valuable time.

Key Features:

  • Infinite Scroll: It is a technique where additional content keeps loading automatically at the bottom of a web page, allowing you to scroll down continuously without navigating to the next page. It is also known as lazy loading, and ParseHub utilizes it to extract data for you.
  • IP Rotation: ParseHub distributes requests for web crawling across multiple IP addresses. The tool carries out the IP rotation practice while fetching data for you to prevent rate limits. It ensures that your IPs are not blocked by websites, allowing you to get the information you desire with a different IP address each time.
  • REST API: This web scraping tool’s API is designed with REST principles, utilizing HTTP verbs and predictable URLs whenever possible. It allows you to control and execute your scraping projects with ease.
  • Image Scraping: Image scraping is a method that involves extracting image data from online sources in formats like JPEG, PNG, and GIF. ParseHub can assist you in scraping images from social media platforms and e-commerce websites by extracting the URL for each image on a webpage.

Pricing: ParseHub has a free plan which you can download easily. There are two monthly paid plans: the Standard at $189 and the Professional at $599. You can also choose a customized ParseHub Plus plan to deploy it for your entire enterprise.


Image Source: ScrapingBee

ScrapingBee is one of the well-known APIs for web scraping. This tool runs JavaScript on web pages and seamlessly changes proxies with each request, ensuring your access to HTML pages without encountering any blocks. ScrapingBee offers different APIs for managing a wide range of tasks, such as extracting customer reviews or comparing prices of different products. It also provides you with a specialized API for scraping Google search results. 

Key Features:

  • SERP Scraping: Scraping a Search Engine Results Page (SERP) can be challenging due to the presence of rate limits. ScrapingBee simplifies this cumbersome process by offering you a Google search API.
  • Result Export Options: This web scraping tool supports export results in JSON, CSV, and XML formats. It is also compatible with other web scraping platforms such as ParseHub, Octoparse, and more. These integrations help you to scrape more data from other sources. You can export your data into the format you wish on ScrapingBee and use the file to conduct data operations.
  • Capturing Screenshots: ScrapingBee has a unique Screenshots API that assists you in capturing full-page and partial screenshots of a website. You can simply screenshot a portion of the website instead of scraping its HTML.

Pricing: ScrapingBee offers four monthly pricing plans that have varying API credits and concurrent requests. The Freelance and Startup plans commence at $49 and $99, respectively. The Business plan charges you $249, while the Business + plan starts at $599.

How does Airbyte help you Leverage Web Scraping Data Further?

Web scraping tools are crafted to gather large quantities of data in varying formats. However, once you have extracted all the data, you need to understand every part of it holistically. The best way to manage the obtained data effectively is to load it into a cloud data warehouse or Big Data platform.

The quickest way to move your dataset into a data warehouse is through data integration and replication platforms like Airbyte. With this platform, you get the flexibility to extract data from not one, but multiple sources. Airbyte has a diverse array of 350+ pre-built connectors. You can choose the destination of your choice and set up a robust data pipeline in only a few minutes. 

Once your data obtained from web scraping tools is loaded into a data warehouse of your choice, you can perform subsequent data analysis. Thus, you can extract the maximum value from your web scraping process and make data-driven strategies for your organization.

Final Takeaways

Web scraping is an effective way to gather relevant and trending information on customers, competitors, and reviews. Initially, it may have been a manual and labor-intensive process. But with the advent of automated web scraping tools, you can streamline and expedite complex data extraction in no time.

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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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 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 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 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.


    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 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 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 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 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 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 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.


    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

    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.