Ingestion Game-Changer: Ramp Accelerates Financial Data Reliability with Matia

Ramp faced ETL system issues affecting key processes. With Matia, data syncs dropped from 3.5 days to 4 hours, boosting continuity and productivity.
Matia Team

Company: Ramp
Location: New York City
Industry:
Fintech
Employees: 1,000+
Solutions: Ingestion
Website: ramp.com

The Data Stack:

  • Ingestion: Matia
  • Warehouse: Snowflake
  • Transformation: dbt , Airflow
  • Other tools mentioned: Looker

The Company

Ramp is a financial operations platform that builds software and financial products to help companies save time and money across complex finance workflows. Their product lines include a corporate card and expense management solution, a Bill Pay product for automating accounts payables, and other products that automate various aspects of managing company spend.

Ramp's data platform team, led by Ryan Delgado, Director of Engineering, focuses on building infrastructure and tools that enable the company to realize business value from data for offline analytics (reporting and business intelligence), online analytics (optimizing analytics in the app), and machine learning (model training and serving).

"Matia powers many of our critical analytics and operational processes across product, GTM, and more. It's critical to how we run our business and measure the usage of our product." - Ryan Delgado, Director of Engineering, Ramp

The Challenge

Like many companies in the financial services industry, data movement is essential to  Ramp’s infrastructure, including critical functions like product development and risk analytics. Ramp was moving a significant amount of data to its Snowflake instance. 

As they scaled, their legacy ETL tool began to show significant limitations. The system suffered from poor reliability and fault tolerance, leading to critical business disruptions. Historical data resyncs were painfully slow, taking up to 3.5 days and deteriorating over time.

Furthermore, during these critical business outages, Ramp did not always receive one-on-one product support. 

The Solution

While searching for a faster, more reliable solution, Ramp was introduced to Matia.

 Key aspects of Matia included:

  • Reliable Postgres Syncs: Matia provided a more reliable solution for syncing Ramp data to Snowflake without disruption.
  • Faster Historical Resyncs: Matia significantly reduced the time required for historical resyncs, improving fault tolerance.
  • Responsive Support: The Matia team proved to be extremely responsive with technical questions and support, often reacting to support requests within minutes.
  • Product Velocity: Ramp was impressed by Matia's ability to quickly develop and launch new products and features. 

The Impact

Since adopting Matia, Ramp has experienced significant improvements in its data operations:

  1. Increased Reliability, Fault Tolerance & Sync Speed: Ramp can now restore their most business-critical syncs in as little as 4 hours, compared to 3.5 days with their previous solution.
  2. Improved Business Continuity: The faster syncs and resyncs have enhanced Ramp’s operational resilience and minimized disruptions of critical processes. 
  3. Enhanced Productivity: With more reliable data pipelines, the data and engineering  teams can focus on value-add work rather than troubleshooting connection issues.