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Feature image Data pipeline tools

Top 5 Data Pipeline Tools in 2022

By Laurent Mauer · July 12, 2022 · 6 min read

As the number of SaaS applications used by companies (from 8 in 2015 to +100 in 2021) and volumetry of data sources (+180 zettabytes of data by 2025) grow in your organization, it becomes difficult to efficiently manage all of them and extract value from them.

You also need to ensure that all the data is secured and that you store it in a safe manner, especially when sensitive data is involved.

A data pipeline is a tool for solving these problems in an efficient way.

A data pipeline tool is a software that automates the task of extracting, transforming, and loading (ETL) data.

It acts as a conduit between different systems so that data can easily be moved around without requiring any manual intervention.

Let’s dive into the different Data Pipeline Tools available and the best way to get the most out of it.

What is a Data Pipeline Tool?

Businesses produce and consume a siloed and diversified amount of data.

As such, several types of data pipelines exist to move data from one point to another, the most well-known data pipeline configuration is to perform an ETL process:

  • Extract data from different sources, often SaaS Applications
  • Transform your extracted data by cleansing and enriching it
  • Load the transformed data in your destination (Data Lake or Data Warehouse)
 

Also, you can do the other way around by extracting data from your Data Lake or Data Warehouse and syncing it to the tools used by Operational teams to activate them in their daily operations, this process is called reverse-ETL.

Better, a Data Pipeline Tool helps you to migrate data from any source to another, from a given Data Warehouse to another one but also from multiple SaaS applications to another one.

In nutshell, a Data Pipeline Tool is a cloud-based or an on-premises data solution that can be used to enhance the performance and scalability of data warehouses and analytical solutions through an automated and optimized sequence of processes used to extract data from different sources, transform and clean it, store it in a central location, then distribute it to where it is needed. 

A Data Pipeline Tool requires you to use SQL and/or Python programming languages in order to transform, merge and load the data from different databases into its warehouse.

List of top 5 Data Pipeline Tools

1. RestApp

RestApp is the next-gen Low/No Code Data Pipeline Tool to activate your data with a modern visual interface, here’s the complete guide to use it.

RestApp not only integrates with any sources and destinations via No Code connectors but also lets you model and transform your data with a graphical user interface in a Low/No Code environment to help you work with any technical and non-technical teammates. 

Benefits of using RestApp: 

  • Free plan & free trials available to get you started.
  • A fair & transparent pricing model that charges users based on the processing time used, not the connectors used nor the number of users.
  • A graphical user interface to simply drag-and-drop SQL & Python functions.
  • Secured & compliant with security standards platform by design (Learn more about Security).

2. Hevodata

Hevo Data, a No Code Data Pipeline that helps to Load Data from any data source such as Databases, SaaS applications, Cloud Storage, SDKs, and Streaming Services and simplifies the ETL process.

The integration with other tools is simple since it is provided with a 3-step configuration to connect to other tools. 

It is a clear choice when it comes to focus on ETL processing tools with a pricing based on lines processed

3. Fivetran

A data integration platform built on a fully managed ELT architecture that provides zero-maintenance pipelines and ready-to-query schemas. It was built to allow data teams to access any data, at any given time.

Easily mapping of data for any given company that wants to fuel data from source to destination.

Key Features:

  • Security: The platform provides security measures by design to keep your data pipeline safe and secure.
  • Processing type: Possibility to be on batch mode or streaming mode.
  • Coding environment: Access data using custom code(Java or Python for instance), so you can build your own connections.

4. Talend

Talend offers an open-source version of its paid-for platform called Data Integration, which transfers data through custom-built pipelines for free.

Various integrations support this process, and the platform’s streamlined UI remains popular in data engineering circles.

Data Integration has its limitations, however. Depending on the amount of data, at some point when data grows, it might be required to upgrade to Talend’s Data Management platform, which requires a fee, to generate worthwhile data analytics and unlock data monitoring and governance features.

5. Stitch

Stitch is a cloud-first, developer-focused platform for moving data.

With businesses having dedicated solutions (CRM, Data Warehouses…), Stitch’s solutions move data to Data & Operational teams in a matter of minutes to work on them.

Stitch connects to various data sources (applications and databases).

Key Features:

  • Integration: The platform helps extract data from various sources and fuel them into any data warehouse.
  • Control panel: Live evaluation of a user’s experience and businesses can use this insight to their benefit.
  • Security: It helps secure data by establishing a connection to a database by a private network without any firewall infiltrations.

Thanks to a Low/No Code SaaS editor, anyone can analyze various and disparate datasets without being required to write code, Data & Ops teams don’t need to rely on the Tech team to get, process and analyze data.

If you’re interested in starting with connecting all your favorite tools, check out the RestApp website or book a demo.

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Laurent Mauer
Laurent Mauer
Laurent is the head of engineer at RestApp. He’s a multi-disciplinary engineer with experience across many industries, technologies and responsibilities. Laurent is at the heart of our data platform.
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