Data pipeline tools

In this blog, our focus is to throw light on the popular data pipelines tools in the market, and how different tools fit in at various points in the data lifecycle.  

What exactly is a data pipeline? 

A data pipeline refers to a set of tools and processes that enables the automated, secure and reliable movement of data from a source to a destination. These data pipelines are also referred to as ELT tools, since they extract, load and transform data from source to destination.  

What are some characteristics of a modern data pipeline?  

At Merit, we believe the following aspects are a “must have” for any data pipeline:  

  • Secure and reliable movement of data 
  • Low-code Platforms, where it’s easy to setup and move data 
  • Low latency, especially needed for high-volume data migration 
  • Ensure data is fresh, in other words, make sure the data in the destination is in-sync with changes on the source side  
  • Reliable data transformation, so the data is usable “as is” on the destination side  
  • 99.9% uptime, since broken pipelines are counter-productive  

Here’s a list of some of the top data pipeline tools to consider, as you work on modernising your data stack.  


A SaaS data operations platform, helps with complete data pipeline operational cycle management including ETL (extract-transform-load), orchestration and monitoring. The solution can be customised to suit the business needs of an organisation regardless of the size, including startups. Its key features include: 

  • A complete solution for data management from extraction to modeling and storage 
  • It empowers users with control over every step of the ETL process  
  • Easy to design custom workflows (based on business needs) 
  • 200+ connectors to collect data with ease from multiple sources  
  • Advanced security techniques to ensure data protection  


One of the biggest advantages of Etleap is that it requires very low maintenance yet it offers full control to setup the pipelines as per your business requirement. Additionally, it is designed to prevent data loss and is an ideal solution if you are looking for a data pipeline to implement in the AWS ecosystem. Etleap’s key features include: 

  • The ability to simplifying complex data pipelines and make it intuitive to setup for analysts or business users  
  • Etleap’s data modeling capabilities are among the best in the market  
  • By automating the process of ETL and report generation, it makes the overall process of going from data to insight that much more efficient  
  • Monitoring of collected data and controlling the data flow further improves a businesses’ effectiveness at using data  
  • Etleap integrates seamlessly with Amazon Redshift, making it an ideal choice for use in the AWS ecosystem  


A cloud-native, developer-focused platform, it helps with rapidly moving data to end users (both business users and data engineers). By connecting to data sources such as MySQL and MongoDB and linking to tools such as Zendesk and Salesforce, relevant data is replicated to the destination data warehouse used for BI. Its key features include: 

  • Businesses can use Stitch to quickly create and configure integrations 
  • Work well in terms of budgets, especially when a large number of data sources is involved  
  • Businesses can load data from 130+ data sources into their destination data warehouse 
  • Provides a real-time evaluation of the end-user’s experience  
  • Secures data without firewall infiltrations by connecting to the database using a private network 

Open-Source Data Pipelines like Apache Kafka 

Often, the best technology solutions are open source. According to a Merit expert, “Our enterprise customers often request open-source tools. This is not only for financial reasons (open-source tools are cheaper and better in terms of budgets) but also because of the robustness of the underlying technology.”  

Tools like Apache Kafka and Apache Airflow are often the data pipeline tools of choice, especially when large-scale data movement is needed. Some of the key advantages of using open-source data pipelines include: 

  • The business gets complete control over the software and users can customise the solution based on their unique needs  
  • Some of these open-source tools have been developed at the world’s most technologically advanced companies. For instance, Kafka was originally built at LinkedIn 
  • Ideal for very large-scale, real-time data movement  


This one is a data pipeline tool specifically designed for customer data. It makes it easy for enterprises to unify customer data from several customer touchpoints, and is extremely popular in sectors such as banking, financial services and retail.  

With Segment, data can be collected from mobile apps, websites, in-store point-of-sale terminals and eCommerce platforms. This data can be used to run personalised marketing campaigns, use customer data better to drive product innovation, etc. Its key features and capabilities include: 

  • Segment Persona helps increase efficiency of advertisements by analysing ROI data as well as break it down for the sales and support team 
  • Ability to run A/B tests to understand which customer campaign is working better  
  • Creating Retention Analysis by analysing the user’s steps on the platform and optimising a business’s funnel to increase conversions 
  • Notifying different tools called Destinations by generating messages about real-time updates on websites and apps and formatting it. 
  • Automated Compliance with the GDPR and CCPA  


Fivetran delivers ready-to-query schemas and zero-maintenance pipelines with automated data integration built on a fully managed ELT architecture. It provides analysts with access to any data, anytime, allowing faster replication of applications and maintaining a high-performance cloud warehouse. Its data mapping feature enables businesses to map their data sources with the destinations and it can support large lists of incoming data sources. Its key features and capabilities include: 

  • Fivetran’s standardised schemas and automated pipelines let analysts focus on analysis rather than ETL 
  • It allows faster analytics of data, including newly added data sources 
  • Its defined schemas and well-documented ERDs (Emergency Response Data Sheet) do not require training or custom coding and allow access to all data in SQL 
  • It is SOC 2 and GDPR compliant, guaranteeing high-level of data security with data encryption 
  • It allows data replication with less or no IT skills through automation of processes. 

Other popular data pipeline tools include Apache Spark, Xplenty, Hevo Data and Confluent.  

Merit Group’s expertise in Data Pipelines and ETL   

Merit Data and Technology partner with some of the world’s leading B2B intelligence companies within the publishing, automotive, healthcare and retail industries. Our data and engineering teams work closely with our clients to build data products and business intelligence tools that optimise business for growth.   

Our data engineers can help you with faster time-to-insights by helping your organisation choose the right data pipeline and data movement architecture, based on your specific business needs.  

Weconsult closely with our clients’ CIOs and technology decision-makers to design the data pipeline architecture that will be support budgets, project timelines and other specific requirements.   

If you’d like to learn more about our service offerings or speak to a data science expert, please contact us here:

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