Boomi vs. Matillion – Overview
About Matillion:
Matillion began as a self‑hosted platform (Matillion ETL), deployed in the customer’s own environment using a VM. While this gave users full infrastructure control, it came with higher operational costs – teams had to provision and manage infrastructure themselves.
In 2023, Matillion released the Data Productivity Cloud (DPC), a managed, cloud-based platform offering. However, many Matillion customers still rely on the self-hosted version of Matillion ETL.
About Boomi Data Integration:
Boomi Data Integration (formerly Rivery) is delivered in one unified, fully managed SaaS platform. Ingestion, CDC, schema drift management, transformation, orchestration, reverse-ETL, and monitoring all happen in a single service – reducing complexity and accelerating delivery.
Boomi Data Integration is also fully integrated in the Boomi Platform, so data teams can manage pipelines in the same workspace where their organization already handles application integrations, APIs, and AI agents. By living inside Boomi’s broader integration fabric, Boomi Data Integration lets customers oversee data movement, app-to-app integrations, API management, and more from a single platform – eliminating context-switching and simplifying governance.
Comparison Snapshot
Capability |
Boomi Data Integration |
Matillion |
| Platform Scope | Boomi Data Integration fully unified within the Boomi platform which includes iPaaS, MDM, EDI/B2B, APIM, AI Agent Management and more. |
Standalone ELT/ETL solution |
| Native Connectors | 200+ managed connectors | ~180 in DPC |
| Supported Targets | Supports wide-range of over a dozen targets including Snowflake, BigQuery, Databricks, Redshift, Azure Synapse, and nearly a dozen more | Primarily Snowflake, Databricks, and/or Redshift as targets within DPC Designer, with limited ability to easily switch targets |
| Custom Connectors | Data Connector Agent – Connect to any REST API using Gen‑AI Agent, 30 × faster than traditional low-code approaches | Traditional low-code approach with limited options |
| Deployment | 100 % Fully-Managed SaaS | Legacy self‑host (Matillion ETL)
Hybrid/managed (DPC) |
| Transformation style | SQL / Python‑first – maximizing flexibility, portability, and agility | Primarily GUI-based for non-coders |
| CDC | Yes – covering many key sources; straightforward to setup and manage | Complex – often requires client-managed CDC agent, adding cost and complexity |
| Advanced Orchestration | Yes | Yes |
| Reverse ETL | Yes | Yes |
| Data Model templates (kits) | 100+ pre-built workflow templates with data models, pipelines, transformations, schemas, and orchestration | Limited |
| Multi‑table replication | Checkbox‑select across tables/schemas | Available in Data Loader (multi‑table input) |
| Automated Schema‑drift | Yes – Automated handling | Automated handling in Data Loader or Streaming connectors; Designer jobs typically require more manual updates |
| Pricing | Pricing is based on true data size or number of runs, differentiated for databases and apps for greater efficiency. | Matillion ETL: Based on server hours
DPC: Credit-based pricing |
| G2 Rating | 4.7/5 | 4.4/5 |
| SAP Data | Easy to use SAP dedicated interface to seamlessly extract all of SAP data. | Limited SAP connectivity options; relies on JCo interface |
| Agentic AI Activation | Built-in AI Agent Management including the ability to create and govern agents | Not available – requires 3rd party solution |
Boomi Data Integration vs. Matillion – Product
Boomi Data Integration
Product Architecture & Deployment
Boomi Data Integration is a unified, fully managed SaaS. All core ELT functions – ingest, CDC, transform, orchestration, reverse ETL, and monitoring – run in one hosted service inside the broader Boomi Platform. There are no VMs, software upgrades, or agents for your team to manage, and governance/security can be applied consistently across data and app integrations.
Connectivity & Extensibility
Boomi includes 200+ managed connectors for popular databases and SaaS apps. The AI‑assisted Data Connector Agent can read REST API docs and generate a YAML‑based connector with advanced controls (eg. chained API calls), speeding up custom connector delivery.
In addition to source connectors, Boomi data Integration supports a wide range of over a dozen targets – including Snowflake, BigQuery, Databricks, Redshift, and Azure Synapse – for flexible, multi-platform data integration.
Transformation Approach
Built around a SQL/Python-first transformation, or optional integrations with tools like dbt or Coalesce. This provides a variety of advantages over primarily GUI-based approaches:
✔️ Greater Control and Speed
✔️ Future-Proof Portability
✔️ CI/CD and DevOps Agility
✔️ Leverages Existing Team Skills
Matillion
Product Architecture & Deployment
Deployment effort varies by product. The newer Data Productivity Cloud (DPC) offers a mostly SaaS experience but still often relies on lightweight PipelineOS agents.
Legacy Matillion ETL is entirely self‑hosted – customers launch and manage a VM image – which means patching, backups, high‑availability, and cloud‑cost optimization fall on your DevOps team – which can add cost and complexity compared to modern fully-managed SaaS models.
Connectivity & Extensibility
Matillion offers ~180 connectors across the platform. Data Loader exposes a curated subset focused on ingestion. For sources without a native connector, the Custom/Flex Connector provides a low‑code UI to configure endpoints, authentication, and schema mapping.
Matillion DPC primarily supports Snowflake, Databricks, and Redshift as native targets within DPC Designer, with limited additional target support through Data Loader.
Transformation Approach
DPC Designer is primarily a drag‑and‑drop, GUI‑first application for transformations. While teams can insert SQL and Python, the code primarily lives within Matillion’s visual framework. This makes jobs easy to design visually but can limit flexibility, portability, and reuse compared to a SQL/Python‑first model.
Boomi Data Integration vs. Matillion – Pricing
Boomi Data Integration
With Boomi Data Integration, pricing is based on true data size or number of runs, differentiated for databases and apps for greater efficiency. Because it’s delivered as a fully managed SaaS, hosting and infrastructure are included – you don’t pay separately for cloud compute to run the service. This makes costs easier to predict and avoids surprise bills tied to VM size, runtime spikes, or maintenance overhead.
Matillion
Matillion uses a credit-based model. In the cloud (DPC), credits are consumed based on how long pipelines run. In the self-hosted ETL product, credits are tied to the size of the instance you run in your cloud (measured in vCores while the VM is on).
With Matillion ETL, there are also indirect costs and added complexity because your team is responsible for patching, scaling, monitoring, backups, and other infrastructure tasks that would otherwise be handled in a managed service.
Boomi Data Integration vs. Matillion – User Reviews
Capability |
Boomi Data Integration |
Matillion |
| Overall G2 Ranking | 4.7 | 4.4 |
| Meets Requirements | 9.3 | 9.1 |
| Ease of Use | 9.5 | 8.2 |
| Ease of Admin | 9.2 | 8.3 |
| Quality of Support | 9.4 | 8.3 |
Considering migrating from Matillion to Boomi Data Integration? Talk to a data expert to jump on the fastest path.