Matillion
Matillion helps data teams integrate and transform data for cloud warehouses.
Matillion is a cloud-native ETL platform that extracts data from multiple sources, transforms it, and loads it into modern data warehouses like Snowflake, BigQuery, and Redshift. The platform uses push-down ELT technology to leverage warehouse compute power for complex transformations on massive datasets. It's purpose-built for each cloud data platform, generating native SQL to maximize performance. Matillion serves mid-market and enterprise data teams who need intuitive, scalable data integration without complex custom development.
Problem solved
Data teams struggle to efficiently extract, transform, and load data from disparate sources into cloud warehouses without building complex custom pipelines.
Target customer
Mid-market and enterprise data engineering teams already invested in cloud data warehouses like Snowflake, BigQuery, or Redshift
Founders
M
Matthew Scullion
CEO & Co-Founder
15 years in commercial IT and software development at European systems integrators; co-founded first startup at 18; AS/400 programmer background.
E
Ed Thompson
CTO & Co-Founder
Provided deep technical architecture expertise to build high-performance cloud data engine.
P
Peter Jackson
Co-Founder
Served as Commercial Director bringing go-to-market expertise.
Funding history
Series A
Not disclosed
September 2016
Led by YFM Equity Partners
· Regional UK investors
Series B
$20M
March 2018
Led by Sapphire Ventures
· Scale Venture Partners, YFM Equity Partners
Series C
$35M
2019
Led by Battery Ventures
· Sapphire Ventures, Scale Venture Partners
Series D
Not disclosed
February 2021
Led by Lightspeed Venture Partners
· SVB
Series E
$150M
September 2021
Led by General Atlantic
· Battery Ventures, Sapphire Ventures, Scale Venture Partners, Lightspeed Venture Partners, Citi Ventures
Later Round
Undisclosed
November 2022
Led by Databricks
· Unknown
Total raised:
$365.7M
Industries
Pricing
Credit-based consumption model with annual fixed packages. Developer, Teams, and Scale editions. Estimated $20K-$35K/year for small teams, $40K-$80K/year for mid-market, $100K-$300K+/year for enterprise. Pay for platform subscription plus separate cloud warehouse compute charges.
Notable customers
Cisco, DocuSign, Pacific Life, Slack, TUI, Western Union
Integrations
Snowflake, Amazon Redshift, Google BigQuery, Azure Synapse, Databricks
Website
Competitors
Fivetran
Broader ELT platform with more pre-built connectors; Matillion focuses more on transformation power and warehouse-native performance.
Airbyte
Open-source alternative with lower cost; Matillion offers more enterprise features, better UI, and tighter warehouse integration.
Ascend
Data integration platform; Matillion's strength is in transformation performance leveraging warehouse compute.
Nexla
Data movement and governance focused; Matillion specializes in ETL/ELT for cloud analytics.
Why this matters: Matillion has established itself as the enterprise choice for cloud data warehouse transformation by combining ease-of-use with warehouse-native performance optimization. With $365M+ in funding from top-tier investors and customers like Cisco and Slack, it's demonstrating that there's massive demand for data integration solutions that aren't just connectors but true transformation platforms.
Best for: Data engineering teams at mid-market and enterprise companies who need fast, scalable data transformation in their cloud data warehouse without writing custom SQL.
Use cases
Multi-source data consolidation
Companies like Cisco consolidated data from dozens of sources into a single warehouse, reducing ETL spend by 85% and simplifying integration management.
Rapid analytics infrastructure launch
DocuSign deployed their entire data integration infrastructure on Matillion in two days, enabling faster data visualization and governance without months of development.
Pipeline maintenance efficiency
Data engineers using Matillion saved 70% of their time managing and maintaining pipelines compared to custom-built or legacy solutions.
Alternatives
Fivetran
Choose Fivetran for breadth of pre-built connectors and simpler setup if you need more data sources; choose Matillion if transformation power and warehouse performance matter most.
Airbyte
Pick Airbyte for open-source flexibility and lower cost; pick Matillion for enterprise support, UX, and native cloud warehouse optimization.
dbt
dbt is transformation-only and requires engineering expertise; Matillion handles end-to-end ELT with visual orchestration for non-SQL teams.
FAQ
What does Matillion do? +
Matillion is a cloud-native ETL/ELT platform that extracts data from multiple sources, transforms it using your data warehouse's compute power, and loads it into modern cloud data warehouses like Snowflake, BigQuery, and Redshift. It provides a visual, drag-and-drop interface for building data pipelines without writing complex SQL.
How much does Matillion cost? +
Matillion uses consumption-based credit pricing with annual fixed packages. Estimates range from $20K-$35K/year for small teams (1-5 users) to $100K-$300K+/year for enterprise. You also pay your cloud warehouse provider separately for compute used during transformations.
What are alternatives to Matillion? +
Top alternatives include Fivetran (broader connector library), Airbyte (open-source option), Stitch (simpler ETL), Ascend (data integration focus), and dbt (transformation-only, SQL-based).
Who uses Matillion? +
Mid-market and enterprise data engineering teams use Matillion, particularly those invested in Snowflake, BigQuery, or Redshift. Notable customers include Cisco, DocuSign, Slack, Pacific Life, TUI, and Western Union.
How does Matillion compare to Fivetran? +
Both are cloud-native ETL platforms, but Fivetran excels at pre-built connectors for SaaS integrations while Matillion specializes in transformation power by pushing compute to your warehouse. Matillion's interface is more intuitive for complex transformations, while Fivetran is simpler for basic connector setup.
Tags
ETL
ELT
data integration
cloud data warehouse
Snowflake
BigQuery
data transformation
analytics engineering
data pipeline