Unified platform for all your data integration needs

Handle all use cases –
ETL, ELT, batch or real-time
Templatized apps for
ingestion and CDC
Pluggable support for
machine learning
Built-in DataOps and
CI/CD capabilities

Pipeline creation, easy-peasy and fun

Create data integration pipelines in minutes with Gathr’s easy-to-use, visual, drag-and-drop UI. Avoid complex setup hassles and effortlessly perform complex transformations with 300+ built-in operators.

Enjoy the flexibility of no-code, low-code, and pro-code on a single platform. Empower data analysts to easily build pipelines, while simultaneously enabling advanced users to solve complex data integration use cases.

Save hours of development effort with Gathr’s automation and reusability capabilities. Automate schema detection, data validation, pipeline inspection, and maintenance. Reuse pipelines, datasets, and operator groups across applications.

Hassle-free management, monitoring, and maintenance

Create, rollback, and manage pipeline versions easily with Gathr’s GIT- integrated metastore. Monitor all your pipelines on a single canvas and prevent downstream issues. Set up smart alerts, receive automated error notifications, and ensure quick resolution with the platform’s step-by-step guide.

Leave all the heavy lifting to Gathr

Native connectors for all sources and destinations

Real-time data modelling and transformation

More than 300 drag-and-drop

Streaming and batch data integration

Automated schema detection

Automated data validation

Complete visibility of the pipeline

No-code pipeline orchestration

Self-healing, fault-tolerant architecture

Unmatched speed and performance

Leverage the high speed and performance of Apache Spark without the hassles of managing the environment. Use Gathr’s in-memory data processing capabilities to process millions of rows of data in minutes and power faster cleansing, quality scoring and enrichment. Run multiple pipelines in parallel on different technologies or clusters to boost data throughput.

Open. Flexible. Future-ready.

Easily build pipelines in just a few clicks with Gathr’s drag-and-drop UI or leverage the platform’s advanced coding capabilities to create complex workflows and operators for your toughest use cases.

Host data on a single cloud, multiple clouds, or on a hybrid environment (on-premises + cloud. Work off one connected database and drive new-age business use cases forward at full speed.

Create robust pipelines on Gathr and host them wherever your database is. Work on any cloud platform of your choice or transition seamlessly from one to the other with a few clicks.

Tap the advantages of proven, open source technologies like Apache Spark and Apache Storm to ensure speed and reliability across your end-to-end data transformation lifecycle.

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 maintainence, 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.

Data integration just got free – forever

Choose between fully-managed SaaS or customize according to your requirements

Start your free trial Schedule a demo