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Powered by AWS, Matillion Data Productivity Cloud with Maia enables teams to deliver AI and analytics-ready pipelines with greater speed and efficiency. Maia brings agentic data engineering to life, augmenting teams with virtual data engineers that design, optimize, and maintain pipelines autonomously.
Matillion integrates natively with Amazon Redshift, Amazon S3, AWS Lambda, AWS Fargate, Amazon EC2, AWS Glue, Amazon RDS, Amazon Athena, Amazon SageMaker, and AWS Bedrock. The platform combines low-code/no-code simplicity, pushdown ELT performance, broad connectivity, and enterprise-grade security and governance.
AWS Marketplace accelerates Matillion adoption with unified billing, rapid deployment, and alignment with AWS Enterprise Discount Programs, helping organizations modernize their data stack and deliver secure, governed data at scale.
Overview
Matillion Data Productivity Cloud and Maia combine a cloud-native data integration platform with agentic data engineering to accelerate every stage of the data lifecycle.
Maia functions as a team of always-on virtual data engineers, automating the design, build, optimization, and monitoring of pipelines. By embedding AI agents directly into workflows, Maia enables teams to scale instantly, move faster, and deliver consistent, high-quality data for AI, analytics, and operational systems.
Powered by AWS, Matillion leverages the full advantages of AWS scalability, reliability, and security.
The platform integrates natively with: Amazon Redshift, Amazon S3, AWS Lambda, AWS Fargate, Amazon EC2, AWS Glue, Amazon RDS, Amazon Athena, Amazon SageMaker, and AWS Bedrock.
With hundreds of prebuilt connectors and the flexibility to create custom ones, Matillion connects to virtually any data source, including batch, bulk, API, reverse ETL, or streaming, across hybrid and multi-cloud environments.
KEY BENEFITS & FEATURES
AUTOMATE DATA ENGINEERING: Accelerate pipeline delivery and reduce manual effort with Maia agentic workflows. Automate build, debug, and maintenance of ELT pipelines in Amazon Redshift, Snowflake, and Databricks. Generate and optimize SQL, Python, and orchestration logic from natural language prompts. Continuously monitor and document pipelines for governance and audit readiness. Scale execution elastically with AWS Fargate and Amazon EC2.
PREPARE AI-READY DATA: Deliver trusted, connected data for AI and machine learning workloads. Ingest and transform structured and unstructured data from Amazon S3 and other sources. Integrate with AWS Bedrock for LLM and generative AI workflows. Automate RAG-ready data preparation, entity extraction, and sentiment analysis. Build AI-ready datasets in Amazon Redshift for training and inference.
MODERNIZE AND CONSOLIDATE THE DATA STACK: Future-proof infrastructure and retire legacy ETL tools. Migrate from Informatica, Alteryx, SSIS, and Talend into cloud-native Matillion pipelines. Consolidate integration, transformation, and orchestration in a single platform. Leverage pushdown ELT to Amazon Redshift for performance and cost efficiency. Use Amazon S3 and AWS Glue for centralized, governed storage and cataloging.
ENABLE SELF-SERVICE ANALYTICS: Empower more users to access, prepare, and share data securely. No-code pipeline design for business analysts; low-code extensibility for engineers. Publish governed datasets for Amazon Redshift, QuickSight, and BI tools. Reduce reliance on specialized IT resources with agent-assisted, self-service workflows. Maintain governance with runtime RBAC through AWS IAM.
DELIVER SECURE, GOVERNED DATA: Distribute data securely across hybrid and multi-cloud environments. Enforce runtime access controls and masking policies via AWS IAM and Unity Catalog. Maintain observability with audit logging, lineage tracking, and version control. Orchestrate governed data flows using AWS Lambda for event triggers. Deliver analytics-ready datasets across AWS and connected platforms.
ACCELERATE ADOPTION THROUGH AWS MARKETPLACE: Simplify procurement and speed deployment with AWS-aligned purchasing. Consolidate Matillion and AWS services into a single bill for streamlined payment. Apply purchases toward AWS Enterprise Discount Program (EDP) commitments. Choose pay-as-you-go, subscription, or contract-based pricing. Track spend and usage with AWS Cost Explorer and AWS Budgets.
Trusted by enterprises including Cisco, EDF, London Stock Exchange Group, and Slack, Matillion with Maia delivers the speed, scale, and trust you need for modern AI and analytics on AWS and across your hybrid data estate.
Highlights
- PRODUCTIVITY: Do More, Faster with Maia. Boost delivery speed with Maia, the Matillion agentic data engineering system. Intelligent virtual data engineers automate tasks, optimize workflows, and scale pipelines for AI, analytics, and machine learning.
- SEAMLESS AWS INTEGRATION: Matillion integrates deeply with Amazon Redshift, S3, Lambda, Fargate, EC2, and Bedrock. Run high-performance ELT pipelines natively on AWS to maximize speed, elasticity, and cost efficiency while staying within your cloud ecosystem.
- ACCELERATE ADOPTION THROUGH AWS MARKETPLACE: Simplify procurement with unified AWS billing, apply spend toward Enterprise Discount Programs, and choose flexible pricing. Centralized governance and faster deployment reduce overhead while aligning costs with cloud strategy.
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Buyer guide
Gain valuable insights from real users who purchased this product, powered by PeerSpot.
Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
Free trial
Try this product free according to the free trial terms set by the vendor.
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Cost/unit |
|---|---|
Usage in cent of the product | $0.01 |
Dimensions summary
Matillion Data Productivity Cloud uses a consumption-based pricing model measured in credits. The platform charges based on actual compute resources consumed during data execution of data pipelines. Matillion's AWS Marketplace integration is carefully designed to allow billing through AWS without sacrificing the power of Matillion's usage aggregation and pricing. This is achieved by computing pricing on the Matillion side and reporting the total due to AWS Marketplace in the form of a usage-based charge that costs $0.01 per unit.
Top-of-mind questions for buyers like you
How does Matillion's credit-based pricing work on AWS Marketplace?
Matillion uses a consumption-based model where Credits are charged based on product usage. When Matillion charges are generated, either through Paygo or contract subscriptions, the total due is reported to AWS Marketplace in the form of a usage-based charge that costs $0.01 per unit.
How can I estimate my monthly usage costs?
Your monthly costs depend on the volume and complexity of your data workflows. Matillion provides monitoring tools to track credit consumption in real-time, and you can start with a small project to understand your usage patterns before scaling up operations.
Vendor refund policy
Refunds are not provided, but you can cancel at any time.
Legal
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Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
Software as a Service (SaaS)
SaaS delivers cloud-based software applications directly to customers over the internet. You can access these applications through a subscription model. You will pay recurring monthly usage fees through your AWS bill, while AWS handles deployment and infrastructure management, ensuring scalability, reliability, and seamless integration with other AWS services.
Resources
Support
Vendor support
Matillion Support is designed to keep your data pipelines running smoothly and your teams productive. Every subscription includes standard Support with access to our highly qualified technical resources for issue resolution, a 24x7 support portal, and knowledge articles to help you troubleshoot and succeed.
For more demanding needs, Matillion offers Premium Support levels including Mission Critical and Mission Critical Plus. These services provide faster response times, proactive engagement, and direct access to a dedicated team of senior support experts. Customers can also benefit from Technical Account Managers (TAMs) who provide best-practice guidance, coordinate escalations, deliver health assessments, and help plan upgrades or new development projects.
Key capabilities include: 24x7 critical issue response with 1-hour SLA for Priority-1 cases. Accelerated response times for urgent issues (Priority-1 and Priority-2). Expert sessions with technical specialists to optimize use of Matillion. Support service reviews and proactive case monitoring to ensure timely resolution. Advanced services such as developer support, release guidance, and environment health assessments.
Matillion mission-critical Support gives you the peace of mind that your team can deliver reliable, AI-ready, analytics-ready data pipelines on time, with the confidence that experts are available whenever you need them.
Learn more at support.matillion.com
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
Updated weekly
Top
25
In Data Warehouses, ELT/ETL
Top
50
In Data Warehouses, ELT/ETL
Top
10
In ML Solutions
Sentiment is AI generated from actual customer reviews on AWS and G2
Functionality
Ease of use
Customer service
Cost effectiveness
Positive reviews
Mixed reviews
Negative reviews
AI generated from product descriptions
Data Integration Automation
AI-powered virtual data engineers that automate pipeline design, optimization, and maintenance using natural language processing
Multi-Cloud Connectivity
Hundreds of prebuilt connectors supporting batch, bulk, API, reverse ETL, and streaming data sources across hybrid and multi-cloud environments
Native AWS Service Integration
Direct integration with AWS services including Amazon Redshift, S3, Lambda, Fargate, EC2, Glue, RDS, Athena, SageMaker, and Bedrock
AI Data Preparation
Automated data transformation capabilities for structured and unstructured data, supporting entity extraction, sentiment analysis, and RAG-ready dataset generation
Governance and Security
Runtime access controls, audit logging, lineage tracking, version control, and integration with AWS IAM for secure data distribution
Data Integration Methodology
Supports both ETL and ELT data integration patterns with codeless visual development interface
Cloud and On-Premises Connectivity
Enables connection to hundreds of cloud and on-premises data sources including AWS services, enterprise applications, and databases
Parallel Data Processing
Utilizes highly scalable parallel data integration architecture for optimized data loading and processing
Connector Ecosystem
Provides multi-tier connectors supporting file systems, databases, cloud storage, and enterprise applications across Tier B, C, and D categories
FedRAMP Compliance
Offers FedRAMP-compliant integration services with specific security and regulatory requirements for government cloud environments
Data Source Connectivity
Secure connection to multiple AWS data sources including Amazon S3, Amazon Redshift, and Amazon RDS
Elastic Compute Processing
Scalable data and machine learning processing powered by Amazon EKS supporting Python, R, Spark, and multiple programming environments
AI Service Integration
Pre-built workflows integrating with AWS AI services like Amazon SageMaker and Amazon Comprehend
Large Language Model Connectivity
LLM Mesh capability for connecting to Amazon Bedrock to support Chat, Retrieval-Augmented Generation (RAG), and Agentic workflows
Collaborative Analytics Platform
Visual platform enabling distributed creation of advanced analytics with collaboration between technical and non-technical teams
Validated by AWS Marketplace
FedRAMP
GDPR
HIPAA
ISO/IEC 27001
PCI DSS
SOC 2 Type 2
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No security profile
No security profile
Standard contract
No
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Customer reviews
4.3
6 ratings
6 AWS reviews
|
85 external reviews
Star ratings include only reviews from verified AWS customers. External reviews can also include a star rating, but star ratings from external reviews are not averaged in with the AWS customer star ratings.
Jitendra Jena
Easy integration and workflow proposals streamline processes
Reviewed on Aug 20, 2025
Review from a verified AWS customer
What is our primary use case?
For the ETL, we are using Matillion Data Productivity Cloud .
We have skilled resources for Matillion Data Productivity Cloud , which is why we are using it. The infrastructure is provided by the customers, and we implement based on their requirements. When customers have a Matillion Data Productivity Cloud license and ask us to use it, we implement it accordingly.
They are helpful for our data integration.
What is most valuable?
The predefined connectors eliminate the need to write code for connectivity. If you have a predefined connector, it is easy to use with plug and play functionality.
The processing time and ease of use are significant benefits.
As everyone is moving into AI integration, it will definitely help.
When creating workflows, they can propose solutions directly.
What needs improvement?
The main areas for improvement are AI features and scalability.
For how long have I used the solution?
We have been using Matillion Data Productivity Cloud for the last five to six years.
What was my experience with deployment of the solution?
The deployment process is easy.
What do I think about the stability of the solution?
Stability-wise, it is performing well.
What do I think about the scalability of the solution?
Scalability in Matillion Data Productivity Cloud has some limitations. Depending on the nature of data sets, volume, and mixture of different data, the scalability could be improved as manual code writing is still required.
It could definitely be more scalable.
How are customer service and support?
The support is good.
How would you rate customer service and support?
Positive
Which solution did I use previously and why did I switch?
Previously we worked with Microsoft SSISÂ . SSISÂ is an older technology, while Matillion Data Productivity Cloud is more advanced. Each solution has their own advantages and disadvantages.
What was our ROI?
We have experienced both time savings and money savings.
What's my experience with pricing, setup cost, and licensing?
The pricing is managed by the tooling team. The pricing is moderate, neither expensive nor cheap.
What other advice do I have?
We are working with JMeter but not with other Apache products.
We cannot use open-source solutions due to compliance issues.
We work with AWSÂ , primarily using Redshift and Reltio.
We use both Azure and AWS public cloud services.
I would rate Matillion Data Productivity Cloud a seven out of ten.
Overall, it has been a good experience.
The overall review rating is 9 out of 10.
Which deployment model are you using for this solution?
Public Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Amazon Web Services (AWS)
DIEGOENCINALES
Utilize data systems securely and efficiently while connectivity issues require attention
Reviewed on Apr 14, 2025
Review provided by PeerSpot
What is our primary use case?
I primarily use Matillion Data Productivity Cloud for ingest functions. In one client's case, we switched from typical AWS tools and changed all of the blueprints and architecture to use Matillion Data Productivity Cloud for ingesting information from GCP and reading SQL data.
What is most valuable?
Matillion Data Productivity Cloud is effective for ingest functions, particularly when moving information to Snowflake and performing many transformations. Its integration with existing environments, utilizing security measures like VPN and VPCs, makes it a secure choice. However, its features are not notably different from other products in the market.
What needs improvement?
There are problems with GCP connectivity. Specifically, connections to BigQuery for extracting information are complex, and the optimization of the extraction process requires improvements. I raised this issue with Matillion's support, but the solution is pending with their research team.
For how long have I used the solution?
I have been working with Matillion Data Productivity Cloud for two years.
What do I think about the stability of the solution?
Matillion Data Productivity Cloud is stable and functions reliably as a product.
What do I think about the scalability of the solution?
The autoscale process works well, allowing the system to start another node automatically if the first machine reaches 80% capacity. However, the limitation is the number of parallel jobs due to the direct relation to the cores on the machine.
How are customer service and support?
Matillion's technical support is excellent. They communicate effectively and respond quickly to all inquiries.
How was the initial setup?
The initial setup is straightforward. We completed the foundations process using Infrastructure as Code (IaC ), which standardizes and simplifies the deployment process.
What was our ROI?
In terms of ROI, one client found that using Snowflake tasks was more cost-effective than Matillion's credits cost. Consequently, we adjusted our processes to use Matillion Data Productivity Cloud only for extraction and ingestion, while Snowflake handled all transformations and jobs.
What's my experience with pricing, setup cost, and licensing?
While pricing can be an issue compared to other solutions, Matillion Data Productivity Cloud offers discounts and special deals, especially when dealing with high-volume clients or fewer existing clients in specific regions, like Spain.
Which other solutions did I evaluate?
In many cases, clients consider buying a product from the same hyperscaler for an end-to-end solution, such as Microsoft Fabric .
What other advice do I have?
While Matillion Data Productivity Cloud can be valuable, it is challenging to recommend due to its pricing and limited clientele in regions like Spain. Overall, I would rate Matillion as a six out of ten.
Which deployment model are you using for this solution?
On-premises
Syed A.
Good SaaS ETL Tool
Reviewed on Mar 13, 2025
Review provided by G2
What do you like best about the product?
Matillion's simple UI makes user comfortable to configure and easy to understand the flow. And it's well maintained configuration section is a big plus for this platform. So even new users can easily understand this platform's features and design. Additionally Matillion providing learning materials and courses for beginners to understand their tool and the topics in the course also few, because they teaching only necessary topics which can help beginners to work in their platform as a professional.
What do you dislike about the product?
Matillion doing good in their pathway of Data Engineering, but some drawbacks I have noticed is it's API limitations. Basically Matillion providing API to retrieve metadata from their system, but when it's come to Administrative API's which is something administrator access only features they not provided sufficient APIs for that. And one more dislike in it's designer console, some of the components are working as expected.
What problems is the product solving and how is that benefiting you?
Basically Matillion is a ETL tool which works as usual in the Data Engineering field. But apart from that it has many advantages related to Administrative features. They are having a hub which serves billing data in a decent way. Basically teaching a technology/tool to beginners is a big headache especially in Data Engineering, because here everyone is working on top of data only. If anything goes wrong then the whole production got trouble. So in this scenario Matillion solves the teaching in a simple way as they are providing courses to learn their tools and also they are providing free trials to practice the learning. This is a very good initiative from Matillion. And the courses also very simple and contains required details only about the tool. This will stop beginners to lead to confusions, because of required content.
Jeberson D.
It on e of the easy etl tool to learn.
Reviewed on Dec 10, 2024
Review provided by G2
What do you like best about the product?
Its more use in etl,elt,etlt process I used it for 4 years
What do you dislike about the product?
Its not afree tool that a diske in matillion.
What problems is the product solving and how is that benefiting you?
it transfer json data to table form.
Nikhil L.
Robust ETL Platform with Very Good Cloud Integration
Reviewed on Nov 22, 2024
Review provided by G2
What do you like best about the product?
What I like best about Matillion is its seamless integration with major cloud platforms like AWS, GCP and Azure. This is very user friendly platform for ETL. It's visual interface makes complex workflows look easier. It offers great scalability, making it suitable for big and small scale users. It helps to reduce the complexity of ETL Process with its no code working ability.
What do you dislike about the product?
One area where Matillion could improve is making complex data sources more streamlined for integrations. Also It's pricing model, It become much more expensive when data volume grows.
What problems is the product solving and how is that benefiting you?
Matillion simplifies the ETL process. It allows us to complete complex data pipelines without needing coding expertise. It solves the problem of transforming large data volumes from various sources and loading in cloud data warehouse with ease. It solves seamless integration with cloud platforms like AWS, GCP and Azure.