Best Data Extraction Tools of 2022

To populate your data warehouse with accurate and actionable data, you first need to extract that data from the applications where it originates. That’s why a data extraction tool is a critical piece of your data stack

The best data extraction tools offer seamless integration with your most critical business applications, from your marketing platform and CRM to social media and eCommerce platforms.

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Here are some of the best data extraction tools you can use for your business. 

Fivetran

Fivetran is an industry leader for good reason. The breadth of data connectors that Fivetran offers covers virtually every base and means that no matter how much your company is projected to grow and how many different tools you add, Fivetran will almost certainly be able to continue offering support. Fivetran also includes automatic and continuous data pipeline updates, meaning you don’t ever have to worry if your data is up to date. Fivetran also boasts 99.99% uptime, which means you don’t have to worry about the service going down when you need it most.

We believe in giving our customers best-in-class tooling, and that’s exactly why Mozart Data has partnered with Fivetran to offer 300+ data connectors.

Pros

  • Hundreds of out-of the-box connectors
  • Near real-time data availability
  • Straightforward to set up
  • Coding not required

Cons

  • Custom connectors may be slow to materialize
  • Not the lowest cost option

Stitch Data Loader 

Stitch Data, an ETL service owned by Talend, offers data extraction specifically designed for developers. Stitch connects to over 130 sources and doesn’t require any coding to set up or use. With prices starting at just $100 per month, Stitch is a competitively-priced option that still offers many features.

Pros

  • Good customer support
  • Simple to implement
  • Helpful documentation

Cons

  • Not as many sources as some companies may need
  • Difficult to troubleshoot connection issues
  • Becomes costly with company growth

Hevo Data

Hevo Data is a data pipeline platform that requires virtually no coding to create data extractions from over 100 different integrations, pulling that data directly into your data warehouse of choice. 

One of the unique features of Hevo is its bi-directional nature. It offers both ETL and reverse ETL, allowing you to load clean data from your data warehouse back into applications, so you can more effectively leverage that information. 

Pros

  • User-friendly from the start and fast to set up
  • High-quality customer support
  • Requires almost no code
  • Supports ETL and reverse ETL

Cons

  • Not as many integrations as some companies need
  • Not the best user interface
  • Limited control for scheduling run times, which can be inconvenient

Dataddo

Dataddo bills itself as a data integration platform. A great solution for small businesses, Dataddo doesn’t require a data warehouse to perform data extraction and can load data directly into a data visualization tool like Tableau or even Google Sheets. Like many of the other solutions covered here, Dataddo requires no code to set up and use, making implementation simple. 

Dataddo syncs data every five minutes and offers loading of historical data with all plans, ranging from one year for a standard plan to an unlimited amount of historical data for enterprise-level plans. 

Pros

  • Able to create custom connectors
  • Excellent customer support
  • Easy-to-understand UI

Cons

  • Not as many connectors supported as other tools
  • Pricing per dataset can add up quickly
  • Historical data can be time-consuming to load

Altair Monarch

Altair Monarch offers data extraction capabilities but calls itself a “self-service data preparation solution.” The Monarch tool is a downloadable desktop software that converts data from a range of sources into a usable rows and columns format. 

Unlike some other data extraction options, Monarch is a tool with more than 30 years of operations, meaning some features are much more mature than other data platforms. It also uses data extraction methods to get data from PDFs, which may be important to some businesses. You can choose to process data manually or using the tool’s automator. 

Pros

  • Ease of use in parsing text or PDF docs
  • Ability to extract and parse many types of data
  • Regular customer webinars to expand knowledge of the tool

Cons

  • Not cloud-based
  • UI is outdated
  • Initial learning curve is steep

Portable

Portable specializes in building new data connectors quickly, so data sources that aren’t supported by most data extraction tools can be supported in a matter of days. This type of connectors are often called long tail connectors. Portable is another data extraction solution partner of Mozart Data. Although Fivetran offers a huge range of data connectors, we recognize that not every application can be supported since new tools are launched almost daily. 

Pros

  • Experts at building custom data connectors
  • Short lead time for custom connectors
  • 24×7 monitoring

Cons

  • Potentially expensive option if a large number of connectors are required
  • Focus on long tail connectors makes Portable less useful as a primary ETL tool (do not support some common connectors)

Airbyte

Airbyte is an open-source data integration tool. Airbyte says they “unify your data integration pipelines” into a single platform. Because it’s open source, there is an emphasis on being able to build your team’s own custom connectors and maintaining complete control over your data. 

Pros

  • Can be used for free, although premium features are available
  • Sizeable range of built-in connectors
  • Custom connectors can be built as Docker containers, meaning you can choose which programming language you use to build them

Cons

  • Some reliance on community updates, which can be risky
  • Less app support, more DIY

Keboola

Keboola is an end-to-end ETL tool, offering a data stack as a service application that includes robust data extraction capabilities. Keboola is designed to make data management easier by bringing multiple tasks into one tool and automating critical functions so teams can be smaller and spend less time on the administration of tools. 

Pros

  • Intuitive UI
  • Can write transformations in SQL or Python
  • Extensive support library

Cons

  • Some data connectors do not work seamlessly
  • Code is necessary to create transformations
  • May be too robust for users only seeking a data extraction tool

Adverity

Adverity is an analytics tool designed to help marketing, eCommerce, and sales teams integrate their data into a single source of truth. Adverity allows users to extract data from over 600 sources and transform siloed data into one format for easy visualization with the platform’s built-in dashboard tool. 

Pros

  • Over 600 data connectors out-of-the-box
  • No code necessary
  • Data visualization tool built in

Cons

  • Documentation could be improved
  • Significant time investment to optimize set up
  • Understanding code is necessary for some advanced features

Supermetrics

Supermetrics is a marketing-specific data tool that allows users to collect marketing data from sources including Facebook Ads, Google Ads, and Google Analytics and import that data into an easier-to-use format like a Google Sheet or Excel. 

Pros

  • Easy to build marketing-friendly dashboards
  • Robust social media connectors
  • Reliable customer support

Cons

  • Fewer available connectors than some competitors
  • Data load time can be slow
  • Cost per license

Getting your data out of silos is critical for truly leveraging all the information your business is collecting on a daily basis. Without a data extraction tool, that process is incredibly time-consuming and manual. 

As an all-in-one data platform, Mozart Data partners with best-in-class solutions. We strongly believe the combination of Fivetran and Portable can meet the needs of virtually every company, and do it well. 

Data extraction is a critical part of the modern data stack, but it’s still just one piece. Learn more about the other components in the Start-Up’s Guide to the Modern Data Stack

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