Clean, structure, enrich, and blend data
in real-time

Prepare data 10x faster

Extract data from multiple sources

Automatically detect data correlations

Rectify duplicates and errors

Restructure and transform

Set up models and workflows

Deliver consumption-ready data

Save hours of coding effort

Ensure faster time to insights

Data preparation for ML and analytics taking ages?

Upgrade your data engineering with next-gen unified data pipelining platform

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Effortlessly enhance data quality

Connect to a wide variety of batch and streaming sources for data preparation. Perform data quality checks and enrich incoming data using self-service operators.

Automatically get an accurate, metadata-driven schema as soon as you load data from any source. Save hours of effort with automated data validation.

Fix any errors with a connector or destination easily in just a few clicks. Resolve common problems instantly, without the need for any coding or IT intervention.

Experience 10x faster data processing, powered by Apache Spark. Seamlessly process as many as 1Mn+ events per second – both on-premises and in the cloud.

Upgrade to a modern data preparation tool today

  • Zero-code
  • Drag and drop
  • 300+ built-in operations
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Enable massive productivity gains

Define data preparation and quality rules without spending hours on hand-coding.

Keep building your data preparation pipeline while simultaneously working on the data.

Continuously track changes to your data as you perform transformations.

Develop test cases and validate your data for accuracy leveraging automation capabilities.

Expert Opinion

Gathr is an end-to-end, unified data platform that handles ingestion, integration/ETL (extract, transform, load), streaming analytics, and machine learning. It offers strengths in usability, data connectors, tools, and extensibilty.

Customer Speak

Gathr helped us build “in-the-moment” actionable insights from massive volumes of complex operational data to effectively solve multiple use cases and improve the customer experience.

Meet Gathr.

The only all-in-one data pipeline platform

  • One platform to do it all - ETL, ELT, ingestion, CDC, ML
  • Self Service, zero-code, drag and drop interface
  • Built-in DataOps, MLOps, and DevOps tools
  • Cloud-agnostic and interoperable
  • Data

  • Change Data

  • ETL/ELT Data

  • Streaming

  • Data

  • Machine

Why Gathr


reasons to upgrade to Gathr

Up your ETL game today.

Take it for a spin or get a 1:1 personalized demo


Unified data integration platform

Unified Data Integration platform

A unified data integration and transformation tool for ETL, ELT, Reverse ETL, CDC, real-time analytics


Built-in machine learning

Built-in machine learning

Enrich data streams and enable advanced analytics with built-in drag-and-drop ML capabilities


Best-in-class streaming analytics

Best-in-class streaming analytics

Analyze the current moment now by integrating batch, micro-batch and streaming data


Self-service, zero-code

Self-service, zero-code

Simple, from start to end – empower tech and non-tech users to build, deploy and manage pipelines in few clicks




Break silos by enabling data engineers, data scientists & ops engineers to collaborate on a single platform


Built-in XOps

Built-in XOps

Accelerate the entire analytics lifecycle using built-in DataOps, MLOps and DevOps capabilities




Get production-ready output from day 1 - extensively tested for scale, security, and stability


Open and extensible

Open and extensible

Quickly adapt to changing technologies with an open and extensible architecture




Designed and built to run in any cloud environment including multi-cloud and hybrid-cloud setup


Lowest TCO

Lowest TCO

TCO less than cost of 1 skilled data engineer – choose from free/ flat/ consumption-based pricing models

Customer Stories

Powering breakthrough success

Learning and Insights

Stay ahead of the curve

Q&A with Forrester

Building a modern data stack: What playbooks don’t tell you


4 common data integration pitfalls to avoid


Why modernizing ETL is imperative for massive scale, real-time data processing

Fireside Chat

Don’t just migrate. Modernize your legacy ETL.