AWS Glue is a managed extract, transform, and load (ETL) service designed to make it easy for customers to prepare and load data for analytics. With it, users can create and run an ETL job in the AWS Management Console. Users point AWS Glue to data stored on AWS, and AWS Glue discovers data and stores the associated metadata (e.g. table definition and schema) in the AWS Glue Data Catalog. Once cataloged, data is immediately searchable, queryable, and available for ETL.
$0.44
billed per second, 1 minute minimum
Matillion
Score 8.4 out of 10
N/A
Matillion is a data pipeline platform used to build and manage pipelines. Matillion empowers data teams with no-code and AI capabilities to be more productive, integrating data wherever it lives and delivering data that’s ready for AI and analytics.
$2.50
Pay as you go per user
Pricing
AWS Glue
Matillion
Editions & Modules
per DPU-Hour
$0.44
billed per second, 1 minute minimum
Developer: For Individuals
$2.50/credit
Pay as you go per user
Basic
$1000
per month 500 prepaid credits (additional credits: $2.18/credit)
Advanced
$2000
per month 750 prepaid credits (additional credits: $2.73/credit)
Enterprise
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Offerings
Pricing Offerings
AWS Glue
Matillion
Free Trial
No
Yes
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
Yes
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
—
Billed directly via cloud marketplace on an hourly basis, with annual subscriptions available depending on the customer's cloud data warehouse provider.
Matillion provided much more flexibility than the other products we tested, at a much lower price point. Other products, in my view, had a cleaner/simpler UI but I also felt that they offered much less functionality. A key design pattern we had to deliver was to perform delta …
The Matillion selection was not my decision. But I think it's a good enough choice. It is especially valuable that the team can learn Matillion easily and that the project can be understood by the entire team with the visual environment instead of complex ETLs.
Removes most of the complexity around setting up and preparing things. If you could describe with words what needs to be done to move data from A to B, the implementation in Matillion would probably be the most similar in terms of simplicity of understanding what you are doing …
Matillion is much easier to set up and easier to work for the team. Offers a lot more connections which are easier to set up. Environment variables make it easy to set up once and job creation is easy. We use Metadata tables to just loop through the list of tables that need to …
When compared with other technologies , Matillion was cost effective , more scalable and flexible in terms of complexity and components. The licensing cost of Matillion was also less and the flexibility with components helps in implementing complex business logics. The training …
Matillion has better documentation, is easier to pick up on, and is better supported. Glue doe shave pyspark though and might handle Big Data more effectively.
It is much easier to use in terms of GUI capabilities. The only reason we would use an ETL tool other than our own manually written SQL scripts, is to be able to allow other engineers to use it without having one domain expert stuck on the inner working of complex scripts. So …
At that time, ~3 years ago, none of the competitors were as easy to start using as Matillion. As our team was not so experienced with ETL, Matillion was the best and easiest way to get our hands dirty with defining pipelines.
It has a drag-&-drop graphical UI, which makes it easy to connect all the components together. It's very fast to set up from cloud marketplace. It supports many data sources and it also provides a customizable data source component.
AWS Glue and Matillion are both software designed to help organizations extract and transform business data. AWS Glue is a data preparation tool, designed to help businesses prepare data for analysis, bypassing a data warehouse when possible. Matillion is a data integration tool designed to help businesses quickly pool together data from multiple sources such as SaaS applications.
Features
AWS Glue and Matillion both provide ETL features, but they also have a few unique features that set them apart from each other.
AWS Glue has support for data lakes, allowing businesses to prepare and integrate raw data and blob files with ease. Additionally, developers can create scripts to integrate data into AWS Glue that isn’t natively supported using Python or Scala. Lastly, AWS Glue helps businesses keep their business data compliant with regulatory guidelines including HIPAA and GDPR, making it a good choice for medical businesses.
Matillion provides built in support for over 40 SaaS applications. This makes Matillion a good choice for businesses with many applications they need to pull data from, particularly if they lack the resources or ability to make custom integrations. Additionally, Matillion provides features for data ingestion and business intelligence.
Limitations
Though AWS Glue and Matillion both help organizations transform data, they also have some limitations that are important to consider.
AWS Glue doesn’t provide built in integrations for SaaS application, though it is possible to build custom integrations. For businesses with limited resources or without a dedicated development team, AWS Glue may not provide enough support for data integration. Additionally, AWS Glue includes some analytics features, but ultimately provides limited business intelligence features.
Matillion offers support for SaaS applications, but doesn’t provide significant support for building out new integrations. Businesses with niche applications that aren’t covered by Matillion may consider other options. Additionally, Matillion offers support for ensuring regulatory compliance, but only for GDPR. Businesses storing medical data may prefer other options that also ensure HIPAA compliance.
Pricing
AWS Glue pricing depends on the needs of the business and the amount of data processes performed. Despite this, AWS does provide some pricing examples so businesses have an idea of what they might be spending, such as this: “$0.44 per DPU-Hour, billed per second, with a 1-minute minimum for each ETL job of type Python shell”. Businesses looking for specific pricing information can reach out to the vendor for a quote.
Matillion pricing similarly depends on the needs of the business, but it starts as low as $1.37 an hour and offers support for Amazon Redshift, Google BigQuery, Azure Synapse Analytics, and Snowflake.
Features
AWS Glue
Matillion
Data Source Connection
Comparison of Data Source Connection features of Product A and Product B
AWS Glue
-
Ratings
Matillion
8.5
143 Ratings
4% above category average
Connect to traditional data sources
00 Ratings
8.9142 Ratings
Connecto to Big Data and NoSQL
00 Ratings
8.2100 Ratings
Data Transformations
Comparison of Data Transformations features of Product A and Product B
AWS Glue
-
Ratings
Matillion
8.6
143 Ratings
7% above category average
Simple transformations
00 Ratings
9.2143 Ratings
Complex transformations
00 Ratings
8.0142 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
AWS Glue
-
Ratings
Matillion
8.3
135 Ratings
6% above category average
Data model creation
00 Ratings
9.133 Ratings
Metadata management
00 Ratings
9.140 Ratings
Business rules and workflow
00 Ratings
8.3126 Ratings
Collaboration
00 Ratings
7.4127 Ratings
Testing and debugging
00 Ratings
7.5128 Ratings
Data Governance
Comparison of Data Governance features of Product A and Product B
One of AWS Glue's most notable features that aid in the creation and transformation of data is its data catalog. Support, scheduling, and the automation of the data schema recognition make it superior to its competitors aside from that. It also integrates perfectly with other AWS tools. The main restriction may be integrated with systems outside of the AWS environment. It functions flawlessly with the current AWS services but not with other goods. Another potential restriction that comes to mind is that glue operates on a spark, which means the engineer needs to be conversant in the language.
Great: Need to query simpler APIs, or utilize well known services such as GSheets etc.? Matillion has got some of the best and easiest to use connectors out there. Not so great: Do you need have a competent CI/CD flow that you will be able to update / compare from Matillion as well as other sources at the same time? Good luck, you will need to be extra careful, as you might have to have a deeper dive into your servers Terminal each time you have a git conflict.
It is extremely fast, easy, and self-intuitive. Though it is a suite of services, it requires pretty less time to get control over it.
As it is a managed service, one need not take care of a lot of underlying details. The identification of data schema, code generation, customization, and orchestration of the different job components allows the developers to focus on the core business problem without worrying about infrastructure issues.
It is a pay-as-you-go service. So, there is no need to provide any capacity in advance. So, it makes scheduling much easier.
Matillion is brilliant at importing data -- it would be amazing to have more ways to export data, from emailed exports to API pushes.
Any Python that takes more than a few lines of code requires an external server to run it. It would be great to have more integration (perhaps in a connected virtual environment) to easily integrate customized code.
Troubleshooting server logs requires quite a bit of technical expertise. More human readable detailed error handling would be greatly appreciated.
With the current experience of Matillion, we are likely to renew with the current feature option but will also look for improvement in various areas including scalability and dependability. 1. Connectors: It offers various connectors option but isn't full proof which we will be looking forward as we grow. 2. Scalability: As usage increase, we want Matillion system to be more stable.
While easy to set up and manage monitoring for large datasets, its complexity can be a barrier for new users. Integration with AWS Ecosystem, Managed Monitoring, Dashboards and monitoring tools for AWS Glue are generally easy to set up and maintain, Automated Data Pipelines. Automates data pipeline creation, making it efficient for certain data integration
We are able to bring on new resources and teach them how to use Matillion without having to invest a significant amount of time. We prefer looking for resources with any type of ETL skill-set and feel that they can learn Matillion without problem. In addition, the prebuilt objects cover more than 95% of our use cases and we do not have to build much from scratch.
Amazon responds in good time once the ticket has been generated but needs to generate tickets frequent because very few sample codes are available, and it's not cover all the scenarios.
Overall, I've found Matillion to be responsive and considerate. I feel like they value us as a customer even when I know they have customers who spend more on the product than we do. That speaks to a motive higher than money. They want to make a good product and a good experience for their customers. If I have any complaint, it's that support sometimes feels community-oriented. It isn't always immediately clear to me that my support requests are going to a support engineer and not to the community at large. Usually, though, after a bit of conversation, it's clear that Matillion is watching and responding. And responses are generally quick in coming.
AWS Glue is a fully managed ETL service that automates many ETL tasks, making it easier to set AWS Glue simplifies ETL through a visual interface and automated code generation.
Fivetran offers a managed service and pre-configured schemas/models for data loading, which means much less administrative work for initial setup and ongoing maintenance. But it comes at a much higher price tag. So, knowing where your sweet spot is in the build vs. buy spectrum is essential to deciding which tool fits better. For the transformation part, dbt is purely (SQL-) code-based. So, it is mainly whether your developers prefer a GUI or code-based approach.
We're using Matillion on EC2 instances, and we have about 20 projects for our clients in the same instance. Sometimes, we're struggling to manage schedules for all projects because thread management is not visible, and we can't see the process at the instance level.
We are using GLUE for our ETL purpose. it’s ease with other our AWS services makes our ROI, 100% ROI.
One missing piece was compatibility with other data source for which we found a work around and made our data source as S3 only, so our dependencies on other data source is also reducing