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 6.8 out of 10
N/A
Matillion is a productivity platform for data teams. Matillion's Data Productivity Cloud helps data teams – coders and non-coders alike – to move, transform, and orchestrate data pipelines with the goal of empowering teams to deliver quality data at a speed and scale that matches the business’s data ambitions. The vendor states enterprises including Cisco,
N/A
Pricing
AWS Glue
Matillion
Editions & Modules
per DPU-Hour
$0.44
billed per second, 1 minute minimum
No answers on this topic
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
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Billed directly via cloud marketplace on an hourly basis, with annual subscriptions available depending on the customer's cloud data warehouse provider.
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.
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 …
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
7.6
123 Ratings
8% below category average
Connect to traditional data sources
00 Ratings
7.7122 Ratings
Connecto to Big Data and NoSQL
00 Ratings
7.582 Ratings
Data Transformations
Comparison of Data Transformations features of Product A and Product B
AWS Glue
-
Ratings
Matillion
7.3
124 Ratings
14% below category average
Simple transformations
00 Ratings
8.1124 Ratings
Complex transformations
00 Ratings
6.4123 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
AWS Glue
-
Ratings
Matillion
7.2
116 Ratings
12% below category average
Data model creation
00 Ratings
9.133 Ratings
Metadata management
00 Ratings
9.140 Ratings
Business rules and workflow
00 Ratings
5.9108 Ratings
Collaboration
00 Ratings
5.5108 Ratings
Testing and debugging
00 Ratings
5.5109 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.
It is very well suited for ETL on the cloud. Whenever there is something that can be accomplished with no code or little code, Matillion is a good tool. However, if your pipeline requires a lot of customizations, Matillion should be avoided.
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.
We leveraged Matillion’s no-code principals to make data manipulation easy for our internal customers. People who don't know how to use SQL no longer need to. Everything in Matillion is self-explained with no or little coding.
We connected Matillion to our data warehouse to allow people to read raw data, transform it, then write results back to their sandbox databases. The drag and drop component design allowed customers to create complex data models at the speed of thought without any risk to production data.
With sharing capabilities between projects enabled, everyone was able to help each other when questions arose which instilled a strong sense of collaboration and community.
I think a non-CLI approach to installing and uninstalling python libraries would be nice. I mean, it isn't difficult to install a python library via Linux or CLI, but I imagine most companies don't feel comfortable allowing Matillion users to go on a virtual server and installing it themselves. Requirement.txt file for installing libraries would be simple, and maybe that could also be used to uninstall libraries as well......or maybe the library gets automatically downloaded if it is imported into a python script but the library doesn't exist.
Python Component is lacking very much in terms of UI. It would be unrealistic for me to suggest Matillion build its own EDI, but it would be nice if a python component could connect to a local IDE. Right now, if you want to write any decent length python code, you are going to be stuck copying and pasting your code from your local IDE.
It is also very difficult to debug in Matillion because you can't set breakpoints. Local IDE integration can resolve that.
I would like to have more templates to copy from for certain simplistic scenarios. For instance, a template for a job that fails which sends an AWS SNS with the Job name, component it failed on, and the error message. It wasn't as simple as I thought it would be to figure out and having to use a shared job for such circumstances can be painful because you have to export a bunch of variables.
There should be a drop down list for Global Matillion variables as it is difficult to remember at times.
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.
It has been easy to train new employees who don't have previous experience with Matillion. It is quite self-explanatory. There are quite a few things that can be done with Python, however, we have not really looked into this feature much but likely will do in the future. Mostly, it is drag and drop of components and environments can be set up so easy to set up connections as well.
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.
Matillion ran circles around Stitch and Striim both in functionality, setup, and performance. There was no real comparison. Fivetran massively outperforms Matillion in pretty much every facet of the production from setup, maintenance, visibility, and usability. It already has the ability to connect any data source to a destination regardless of database type. Why we chose Matillion over Fivetran is that, for our current needs, Matillion provides us with the functionality that we need and a much more competitive price for a smaller company.
I have been able to connect Matillion to AWS Aurora Databases, MySQL databases, Rest APIs, Files in AWS S3, etc. Being able to load all of that disparate data into one datalake has made data mining and reporting a lot simpler. I wish everything could be implemented as easily as Matillion.
