Real-time database replication for
real-time insights

Build CDC applications in minutes using
built-in templates

Easily create apps using a wizard-based assistant

Save 70% development time and effort

Capture databases changes continously

Choose from multiple CDC modes

Enable real-time data warehousing

Seamlessly sync any source with any target

Monitor multiple CDC jobs with ease

Ensure reliable data transfer with zero loss

Legacy ETL failing you?

Upgrade your data engineering with next-gen data integration platform

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Keep your data complete, accurate, and up to date

Use Gathr’s zero-code, drag-and-drop visual interface and pre-built templates to quickly build CDC apps for any use case.

Read changes to both batch and streaming data and push live updates to your data warehouse or lake.

Develop, operationalize, and monitor CDC jobs, with complete visibility of execution time, events, historical runs, and more.



Next-gen platform for
CDC use cases

Supports all popular sources and targets, reads both batch and streaming data in any format.

Gathr automatically validates CDC prerequisites and performs comprehensive checks on the database to maintain ACID reliability.

Built-in mechanism to group CDC tables into one or more jobs for efficient resource utilization.

Multiple CDC modes, ability to choose table and schema attributes, file-based partitioning, and more.

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.