Clean, enrich, and analyze massive-scale data
in real-time

ETL, ELT, reverse ETL – do it all

Streaming and batch ETL/ELT

Built in drag-and-drop ML

Native connectors for all sources & targets

300+ pre-built operators

Data transformation in real-time

Advanced orchestration capabilities

Automated schema detection

DataOps, MLOps, and DevOps tools

Existing ETL data data integration tool not up to the mark?

Upgrade to modern unified data pipelining platform

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10x faster processing powered by Spark

Create batch and streaming data pipelines easily with a visual, no-code interface. Empower analysts to build pipelines regardless of skillsets.

Use Gathr’s native connectors to get started in just a few clicks. Process any data format – CSV, JSON, XML, AVRO, Parquet, ORC, TAP, fixed length data, and more.

Use Gathr's powerful compute engine to effortlessly process more than 1 million events per second – both on-premises and in the cloud.

Up your analytics game with support for ML, natural language processing, anomaly detection, geospatial analytics, predictive modelling, and more.

Simplify stream processing and save development effort

Use pre-built operators to join data from multiple connectors and design SQL join queries without manual coding. Or write custom SQL queries for complex use cases.

Easily configure auto-scaling for all your pipelines. Optimize resource utilization based on conditions like memory, load, container availability etc.

Replace out-of-order/missing data with Gathr’s built-in imputation functionality. Use advanced lookups and table processers to enrich incoming streams.

Leverage our built-in checkpointing mechanism to ensure high availability and fault tolerance. Choose from multiple disaster recovery options to prevent data loss.

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.