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

Legacy ETL failing you?

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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.



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
    Ingestion

  • Change Data
    Capture

  • ETL/ELT Data
    Integration

  • Streaming
    Analytics

  • Data
    Preparation

  • Machine
    Learning

Why Gathr

Why Gathr

TOP TEN

reasons to upgrade to Gathr

Up your ETL game today.

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

1

Unified DI platform

Unified DI platform

Avoid product suite hassles with a unified platform for ETL, ELT, Reverse ETL, CDC, real-time analytics

2

Drag-and-drop ML

Drag-and-drop ML

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

3

Best-in-class real-time

Best-in-class real-time

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

4

Self-service

Self-service

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

5

Collaborative

Collaborative

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

6

Built-in XOps

Built-in XOps

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

7

Enterprise-grade

Enterprise-grade

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

8

Open and extensible

Open and extensible

Quickly adapt to changing technologies with an open and extensible architecture

9

Cloud-agnostic

Cloud-agnostic

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

10

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

Driver profiling and risk assessment

Built an end-to-end analytics application to analyze telematics data in real-time and offer customers dynamic, usage-based insurance plans.

Pre-emptive fault detection in auto parts

Implemented a pre-emptive fault detection solution to help predict malfunction of auto parts, enable on-time maintenance, and ensure fault-free production.

Real-time insider threat detection

Used predictive analytics and machine learning to automatically detect threat scenarios and raise alerts for preventing predicted breaches across sensitive applications.

Superior omni-channel customer experience

Delivered proactive insights to help contact center representatives present customers with relevant and personalized offers across multiple channels.

Real-time business activity monitoring

Enabled 10x faster data processing and efficient, near real-time KPI tracking with an end-to-end solution for data ingestion, transformation, enrichment, and analysis.

360-degree view of the customer

Enabled micro-segmentation and targeting, dynamic marketing campaigns, proactive error resolution, and contextualized customer service in real-time.

Processed 1.5 billion events per day

Modernized legacy ETL frameworks to process over 1.5 billion user interactions per day from multiple real-time feeds and reduce the overall release cycle time.

Real-time call monitoring solution

Improved performance metrics such as call abandonment rate, average speed of answer, and average call length by monitoring call activities in real-time.

Real-time multi-lingual sentiment analysis

Enabled rapid and accurate real-time text categorization and multi-lingual sentiment analysis for massive volumes of data from diverse sources.

Call center agent monitoring solution

Reduced annual call center costs by $5M and improved agent productivity by tracking desktop activities of call center representatives in real-time.

Learning and Insights

Stay ahead of the curve

Q&A with Forrester

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

Blog

4 common data integration pitfalls to avoid

Blog

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

Fireside Chat

Don’t just migrate. Modernize your legacy ETL.