Honeybook builds reliable data pipelines with Matia

Info

Company: Honeybook
Location: San Francisco & Tel Aviv
Industry: Business Services, SaaS
Employees: 300 +
Solutions: Ingestion
Website: honeybook.com

The Data Stack:

• Ingestion: Matia 
• Warehouse: Snowflake
• Transformation: DBT
• BI Tool: Looker
• Orchestration: Prefect
• Connectors Used: MongoDB, Google Analytics, Intercom, Qualtrics, Iterable, and others

The Company

Honeybook is a business management platform designed for freelancers, entrepreneurs, and creative businesses to streamline project management, invoicing, and payments. The company relies heavily on data for its operations, with a robust data infrastructure that includes over 1,200 dbt models. Honeybook's data engineering team, led by Nimrod Milo, manages complex data processes that are crucial for the company's day-to-day operations.’’

“When it comes to reliable data, Matia delivers. From a technical perspective, the product is superior and the velocity with which they are able to ship new features is impressive.” - Nimrod Milo, Data Engineering Manager at Honeybook

The Challenge

As the Honeybook team began to scale, Honeybook's team faced challenges with their legacy ingestion tool’s performance, pricing model, ability to release new connectors, and reliability.

In an attempt to address these issues, Honeybook briefly switched to a new ingestion tool. However, this move proved problematic with reliability issues - many connectors that worked during the long duration POC phase failed during full implementation. They also experienced about 30% data loss when using this solution’s webhooks and the complex architecture made switching problematic. 

The Solution

Honeybook discovered Matia and decided to give it a try. Despite initial hesitation about working with a newer, smaller vendor, the team was impressed by Matia's technical proficiency and responsive support. Key aspects of the solution included:

• Smooth Migration: The transition to Matia was relatively seamless, especially for complex sources like MongoDB. Matia is fully reverse compatible with major ingestion providers - one of the only other ingestion tools to be able to claim this.
• Fast Product  Development: When Honeybook needed connectors that weren't available, such as for Qualtrics and Iterable, the Matia team quickly developed them.
• Reliable Data Pipelines: Matia delivered on its promise of moving data reliably to Honeybook's Snowflake warehouse. The team did not see a loss in data and saw a 30% increase in speed. Webhooks were also reliable with no data lost.
• Cost Efficiency: By switching to Matia and optimizing their data pipelines, Honeybook significantly reduced their data transfer costs.

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“The transition to Matia was incredibly smooth. Matia’s superior engineering combined with their support made the process seamless. Within days, we were fully operational with no disruptions. Their platform has exceeded our expectations, allowing us to focus on data engineers on growth and innovation, rather than dealing with data headaches." – Nimrod Milo

The Impact

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

1. Increased Reliability & Speed: The data team now experiences fewer issues with data transfers and connector reliability. 
2. Fast Database Replication: The team was able to move significant from MongoDB to Snowflake, increasing replication speeds by 30%
3. Improved Productivity: With more reliable pipelines, the data team can focus on value-add work rather than troubleshooting connection issues.
4. Scalability: Matia's platform positions Honeybook well for future growth, with the potential to leverage additional capabilities like reverse ETL, data catalog, and observability. 

Overall, Matia has become an integral part of Honeybook's data infrastructure, providing the reliability, support, and scalability necessary for the company's continued growth and success to help Honeybook better serve its customers.

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