Real-time database replication for
Build CDC applications in minutes using
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
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.
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.
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.
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
reasons to upgrade to Gathr
Up your ETL game today.
Take it for a spin or get a 1:1 personalized demo
Powering breakthrough success
Leading auto insurance provider
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.
Fortune 500 Bank
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.
Major US airline
Superior omni-channel customer experience
Delivered proactive insights to help contact center representatives present customers with relevant and personalized offers across multiple channels.
Fortune 500 mortgage lender
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.
Cable TV and telecom provider
360-degree view of the customer
Enabled micro-segmentation and targeting, dynamic marketing campaigns, proactive error resolution, and contextualized customer service in real-time.
Communication analytics company
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.
LEADING U.S. CALL CENTER
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.
TOP U.S. TELECOM PROVIDER
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.
Leading Wireless & Telecom Service Provider
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
4 common data integration pitfalls to avoid
Why modernizing ETL is imperative for massive scale, real-time data processing
Don’t just migrate. Modernize your legacy ETL.