Boomi vs. Matillion

概要

About Boomi Data Integration

Boomi Data Integration 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 part of the broader Boomi Enterprise Platform, 12x consecutive iPaaS leader, meaning data teams can manage pipelines alongside integrations, APIs, and AI agents rather than operating in a separate data engineering environment. While Matillion revolves around data pipelines. Boomi extends further downstream, with native capabilities for master data, managed RAG, semantic context, and agent management.

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, now since renamed to Maia Foundation and bundled into Maia, its AI-enabled data automation platform.

Matillion now spans two generations: Matillion ETL, still self-hosted and widely deployed, and Maia, delivered as a SaaS or hybrid SaaS offering. Matillion ETL is still supported, however, Matillion endorses a formal Matillion ETL-to-Maia upgrade path covering component conversion, job migration, and eventual decommissioning of the Matillion ETL environment, so new architecture and AI capability operate in Maia.

Comparison Snapshot

Matillion ETL and Maia are shown separately, since the two products now differ on deployment, connectivity, CDC, and AI.

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. Boomi for SAP Solutions adds a low-code path to SAP extraction, replication, and event-based CDC that doesn’t depend on ODP.

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

Beyond ELT: Trusted Data and AI Activation

Boomi Data Integration sits inside a platform that carries data past analytics, without stitching separate tools together:

✔️ Trusted master data and golden records through Boomi Data Hub

✔️ Managed, no-code RAG through Knowledge Hub, from ingestion to retrieval

✔️ Governed semantic context and agent management through Meta Hub and Agentstudio

✔️ AI-assisted development through Boomi Companion, which works with compatible agents such as Claude, OpenAI Codex, and GitHub Copilot

Matillion

Product Architecture & Deployment

Deployment effort varies by product. Maia is offered as SaaS or hybrid SaaS. Hybrid deployments use lightweight PipelineOS agents, while Maia Streaming requires customer-hosted Streaming runners. For CDC, each streaming pipeline requires its own agent.

Legacy Matillion ETL is fully self-hosted. Customers deploy and manage the VM themselves, including patching, backups, high availability, scaling, and the underlying cloud infrastructure costs. Matillion has also removed Matillion ETL’s legacy Manage CDC capability and now directs those customers to Maia Streaming.

Connectivity & Extensibility

Matillion ETL documents 80+ out-of-the-box connectors; Maia documents 150+. Custom API work in Matillion ETL runs through a manual API profile workflow, while Maia offers AI-assisted connector creation. Maia supports four native targets in Designer – Snowflake, Databricks, Redshift, and BigQuery – with Matillion ETL covering five, including Synapse.

On SAP, Matillion’s ODP connector is directly affected by SAP’s restrictions on third-party ODP-RFC access. These restrictions can block Matillion’s ODP-based extraction, pushing customers toward alternatives such as OData, NetWeaver, or JDBC. These alternatives carry trade-offs around bulk extraction, setup, licensing, or required SAP expertise.

Transformation Approach

Matillion ETL 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. Maia layers AI assistance over that model rather than replacing it. Development remains primarily visual, and Maia Team, available in-app and through MCP/API, still produces pipelines within Matillion’s component framework.

柔軟で明確な価格体系

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.

User Reviews

G2 scores below compare Boomi Data Integration with Maia.

By feature category, G2 scores Boomi 9.2 and Maia 8.6 for ETL Tools. Maia has too few reviews to score in Data Extraction, Cloud Migration, or Reverse ETL, where Boomi rates 9.2, 9.1, and 9.0.

Considering migrating from Matillion to Boomi Data Integration? Talk to a data expert to jump on the fastest path.

Boomi Blog, “Boomi vs. Matillion,” published June 1, 2025. Updated August 2026 using Boomi Global Market Intelligence battlecards (Aug 19, 2026) and G2 data captured Aug 27, 2026.