Matillion vs. AWS Glue: Which should you use in 2026?

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Philips
Customer Since:
May, 2023
Caterpillar
Customer Since:
July, 2018
case study
DPD
Customer Since:
August, 2019
7-Eleven
Customer Since:
August, 2017
Samsung
Customer Since:
August, 2021
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Boston Red Sox
Customer Since:
August, 2025
Accenture
Customer Since:
August, 2017
McGraw Hill
Customer Since:
August, 2022

Overview

Matillion and AWS Glue are both popular choices in the ETL space. Below is a detailed, side-by-side comparison of their capabilities, pricing, support, and security to help you decide which fits your data stack.

About Matillion

Matillion offers Hundreds of pre-built connectors for databases, cloud platforms, and SaaS applications, with custom connector creation available through no-code tools

About AWS Glue

AWS Glue offers 100+ data sources including Amazon S3, DynamoDB, RDS, Redshift, and third-party systems

Feature Comparison

Capability Matillion AWS Glue

Data loading

Supports data loading to major cloud data platforms with pushdown architecture, but lacks the granular scheduling and incremental loading optimization for operational workflows

Optimized for AWS targets like S3 and Redshift but limited flexibility for multi-cloud or hybrid environments

Data ingestion

Offers cloud-native data ingestion with hundreds of pre-built connectors and custom connector options, but requires technical setup and configuration within your cloud environment

Connects to 100+ data sources but requires AWS ecosystem lock-in and complex configuration for non-AWS sources

Data transformation

Features both low-code and high-code transformation options with AI integration, though transformations are primarily warehouse-focused rather than operational business logic

Code-heavy approach requires Spark expertise and lacks visual, no-code transformation capabilities

Data replication

Provides data replication capabilities through its ETL/ELT platform, though primarily focused on batch processing rather than real-time operational sync

Serverless scaling handles large volumes but lacks real-time sync capabilities and granular scheduling options

Orchestration

Includes pipeline orchestration and automation within the Data Productivity Cloud, but requires more technical expertise to set up complex multi-system workflows

Pay-per-use billing can become unpredictable at scale with limited workflow automation for business users

Alerts and monitoring

Provides pipeline monitoring and alerting capabilities, but notification systems are basic and lack advanced observability features like detailed lineage tracking or proactive anomaly detection

CloudWatch integration provides basic monitoring but lacks granular pipeline observability and proactive failure detection

Dev QA account

Offers multiple environments for development and testing, but environment management can be complex and lacks streamlined promotion workflows between dev, staging, and production environments

Development endpoints available but billed hourly with no clear separation between dev, staging, and production environments

AI workflows

Basic AI-assisted data engineering through Maia virtual assistant, but AI capabilities are primarily focused on pipeline optimization rather than comprehensive workflow automation or intelligent data routing

Basic generative AI assistance for ETL authoring and Spark job modernization, but AI capabilities are narrow and AWS-centric

API

Limited API management capabilities with basic REST API support, but lacks comprehensive API governance, versioning, and enterprise-grade API orchestration features that modern data teams need for complex integrations

Limited programmatic access through AWS SDK and CLI, but lacks dedicated API for pipeline management or custom integrations outside AWS ecosystem

Source control

Git integration available but requires additional configuration and setup, with version control workflows that can be cumbersome for teams used to modern DevOps practices

No native version control or Git integration - relies on external AWS CodeCommit or third-party solutions for pipeline versioning

Pricing

Matillion

Flexible, scalable pricing with unlimited users and environments - pay only for what you use with predictable ROI, but lacks the transparent fixed-fee structure that eliminates capacity planning uncertainty

AWS Glue

Pay-as-you-go billing by the second or minute with charges for ETL jobs, crawlers, Data Catalog storage and requests, DataBrew sessions, and Data Quality tasks. Development endpoints billed hourly. Costs vary by AWS Region with potential for unpredictable scaling expenses.

Implementation & Support

Matillion AWS Glue

Time to implement

Longer implementation cycles due to cloud environment provisioning, connector configuration, and enterprise security requirements

Weeks to months for production-ready pipelines. Requires AWS infrastructure knowledge, Spark/Python coding skills, and time to configure security policies. Simple jobs may start quickly, but enterprise deployments need significant setup and testing.

Onboarding

Enterprise-focused onboarding requiring dedicated cloud infrastructure setup, technical architecture planning, and specialized training for multiple user roles

Requires AWS expertise and infrastructure setup. Teams need to configure IAM roles, set up development endpoints, and understand Glue's serverless architecture before building first pipeline. Getting started involves learning AWS-specific concepts like crawlers, classifiers, and the Data Catalog structure.

Support

Complex enterprise support structure with multiple tiers and response times that can vary significantly based on subscription level and issue complexity

Relies on AWS support tiers and community forums. No dedicated data integration specialists. Support quality depends on your AWS support plan level, with basic plans offering limited technical guidance for complex ETL scenarios.

Security & Compliance

Matillion

Comprehensive enterprise security framework with SSO, MFA, and RBAC, but requires customer cloud environment management and ongoing compliance oversight

AWS Glue

Inherits AWS security model with comprehensive certifications. Offers VPC isolation, encryption at rest and in transit, and IAM integration. However, security configuration complexity requires dedicated AWS security expertise to implement properly.

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