Matillion EDR is used for data loading. It extracts data from various sources, stages it in a data warehouse environment, and then performs orchestration and transformation jobs to automate processes across different layers of the data warehouse.
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Professional ELT Data Integration Tool
What do you like best about the product?
Rich components for developing Data Integration ETL job. Easy and fast implementation.
What do you dislike about the product?
We have experienced several ELT job performance issues that caused Matillion server no response or ETL jobs hanging issues due to Jython Interpreter issue
What problems is the product solving and how is that benefiting you?
Matillion support provided us the solution for resolving Matillion server performance issue, and Matillion new version upgrade support.
Matillion: Empowering Data Wizards with Drag-and-Drop Magic
What do you like best about the product?
Matillion’s intuitive flow visualization makes orchestrating complex data pipelines feel like painting with digital brushes. The drag-and-drop interface transforms intricate ETL processes into a delightful canvas where connections flow seamlessly.
Matillion’s connectors are like well-fitted puzzle pieces. They effortlessly link disparate data sources, allowing you to focus on insights rather than plumbing. Whether it’s cloud services, databases, or APIs, Matillion’s connectors are the bridge to your data dreams.
In a nutshell, Matillion combines creativity and convenience, turning data wrangling into a captivating symphony. 🎨🔗✨
Matillion’s connectors are like well-fitted puzzle pieces. They effortlessly link disparate data sources, allowing you to focus on insights rather than plumbing. Whether it’s cloud services, databases, or APIs, Matillion’s connectors are the bridge to your data dreams.
In a nutshell, Matillion combines creativity and convenience, turning data wrangling into a captivating symphony. 🎨🔗✨
What do you dislike about the product?
Implementing code versioning within Matillion can be a bit like untangling a digital yarn ball. The lack of straightforward integration with popular version control systems can leave users yearning for a simpler path to track changes and collaborate seamlessly.
What problems is the product solving and how is that benefiting you?
ingestion and transformation of raw brons data towards the gold layer.
Matillion ETL - Cloud ETL Tool integrated with Snowflake
What do you like best about the product?
Very Intuitive
Ease of Integration
Ease of Implementation
Ease of Integration
Ease of Implementation
What do you dislike about the product?
Missing features for GIT Integration
Some bugs when coding related to character sets
Some bugs when coding related to character sets
What problems is the product solving and how is that benefiting you?
ETL for Enterprise Data Warehouse
ETL Tool for Operational business processes
ETL Tool for Operational business processes
Offers good user interface and easy to navigate
What is our primary use case?
How has it helped my organization?
It serves as a development environment to build data pipelines. This is part of the entire data integration process, encompassing extract, transform, load (ETL) actions. It's used to run transformations on ETL data, preparing it for consumption.
We had a customer with on-premise systems. We extracted data from these systems and staged it in S3 or Azure Blob Storage. Then, Matillion picked it up for processing. The key advantage here was the speed of development.
What is most valuable?
The new version with the Productivity Cloud is very simple. It's easy to use, navigate, and understand.
It also offers automated scalability in terms of handling large data volumes. It scales up automatically in the background, so you don't have to worry about infrastructure to do that.
What needs improvement?
One of the features that's in development is data privacy in the cloud, along with further SAP integration.
For connectivity to SAP systems.
For how long have I used the solution?
We have been using it for two years. We work with the latest version.
What do I think about the stability of the solution?
I would rate the stability a nine out of ten. It is a very stable solution.
What do I think about the scalability of the solution?
It scales automatically in the background. Obviously, we don't need to take care of any infrastructure for scaling. It scales based on the volume and processing required.
You can tweak it if you want, but it adjusts the scales as needed. So, for smaller workloads, there's less consumption, but for large workloads, it scales to run within a specific SLA.
In South Africa, we've got six large enterprise customers. I would rate the scalability a ten out of ten.
How are customer service and support?
The customer service and support are very responsive.
How would you rate customer service and support?
Positive
Which solution did I use previously and why did I switch?
Our experience is mainly around using Snowflake Data Cloud with Matillion. And the two of them combined, offer superior performance and price point benefits.
Using them together is very efficient because Matillion's processing and Snowflake's own scalability and consumption based on pushing down code work well together. They are very efficient.
We've used Azure Data Factory (ADF) for integration. So that's an alternative, depending on customer choice for the integration. And then on AWS, a few of the other services, like Terraform, and S3 storage, and that's about it.
It's on a case-by-case basis. If they've chosen ADF as a technology, then we implement using that choice.
How was the initial setup?
There is nothing complex in the process. There is a tenant set up by Matillion in a few minutes, and then you can start working.
What about the implementation team?
We are system integrators. We handle the implementations for our customers.
We have around 25 engineers on our team.
What's my experience with pricing, setup cost, and licensing?
The pricing depends on what edition the customer opts for. For example, a standard edition and then business critical of different editions. Each of those has a different cost per unit, which is Italian cost. It is like a utility model model. For example, the standard edition is priced at $2.00 per credit. And you are only charged when you use it. You're not charged when it's idle.
So, the customer only pays for the runtime, not for idle time.
So, the unit cost includes everything, even any additional costs.
What other advice do I have?
Overall, I would rate the solution a nine out of ten.
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)
Matillion is a great ETL tool for cloud data warehouses
What do you like best about the product?
Capability to connect with all the top data warehouses like bigquery, redshift, etc.
The tool is developer friendly, it also provides the capabilities to use python runtime, http end points etc.
The tool is developer friendly, it also provides the capabilities to use python runtime, http end points etc.
What do you dislike about the product?
Re usability of template is a bit challenging. I tried to create a data quality reusable template, but it requires a lot of efforts to make it right.
What problems is the product solving and how is that benefiting you?
Complete data integration in gcp is done via Matillion. Reading from gcs to writing to big query and applying transformations.
Lead data analyst
What do you like best about the product?
It's point in click interface and host of component s that can connect to third-party services makes it very easy for more junior analysts to get involved in ETL workloads.
What do you dislike about the product?
Because of the point and click interface, it lacks flexibility that other more code heavy solutions offer.
What problems is the product solving and how is that benefiting you?
It has really helped bring together disparate data sets and transformed all under one roof that can feed our business intelligent solutions.
Used for wrangling or transforming data from sources like S3 and Databricks
What is our primary use case?
I use Matillion ETL for wrangling or transforming data from sources like S3 and Databricks.
What is most valuable?
The most valuable feature of Matillion ETL is the UI experience in which you can drag and drop most of the transformation.
What needs improvement?
Sometimes, we have issues with the solution's stability and need to restart it for three weeks or more. There is some room for improvement in job clusters for Databricks.
For how long have I used the solution?
We have been using Matillion ETL for three years.
What do I think about the stability of the solution?
Sometimes, we have issues with the solution's stability and need to restart it for three weeks or more.
I rate Matillion ETL an eight out of ten for stability.
What do I think about the scalability of the solution?
Around 100 users are using the solution in our organization. There is a possibility of creating multiple nodes for the solution. However, you need to manage the separate nodes and upgrade the Linux, which is difficult.
I rate the solution an eight out of ten for scalability.
How are customer service and support?
The solution's technical support is great. They respond within a few hours and close the case as soon as possible.
How would you rate customer service and support?
Positive
Which solution did I use previously and why did I switch?
I previously used Informatica PowerCenter and Informatica Cloud. We switched to Matillion ETL because it was cheaper.
What's my experience with pricing, setup cost, and licensing?
Matillion ETL has a pay-as-you-go pricing model of a few dollars per hour of runtime.
What other advice do I have?
I am using the latest version of the solution. The solution's connectors saved us the most time during data transformations.
Overall, I rate the solution a nine out of ten.
Efficient data integration and transformation with seamless cloud-native integration
What is our primary use case?
We use it primarily for transferring data into our cloud data warehouse and conducting research. We rely on Matillion ETL for our data integration and transformation needs, finding its user-friendly interface and robust capabilities highly effective. Essentially, we've built a cloud-based data platform using Matillion ETL to seamlessly extract data from various sources, perform necessary transformations, and store it in our cloud environment.
In our finance-focused projects, we predominantly utilize Matillion for data warehousing tasks, particularly in the realms of finance and micro-lending. While our projects may not involve big data volumes, they often entail handling intricate datasets that require sophisticated processing.
How has it helped my organization?
The cloud-native design of Matillion has significantly impacted our video data workflows, providing a unified view across multiple data sources and serving as a centralized and secure platform. It offers a seamless experience, consolidating various functionalities into one interface, which simplifies our tasks considerably. Moving forward, we're eager to explore their SaaS offering, particularly for Redshift, once it becomes generally available. This scalable solution eliminates concerns about version upgrades, maintenance, and patching, offering a hassle-free experience.
Its versatility is impressive, as it allows us to seamlessly transition between different cloud platforms without being locked into a specific provider.
What is most valuable?
It is an incredibly user-friendly and intuitive tool, making the learning curve quite smooth. Its simplicity is such that one only needs a basic understanding of ETL processes to become proficient. With a plethora of connectors available, it seamlessly integrates with various data sources. Moreover, its native integration with AWS enhances its efficiency, utilizing lightweight instances and pushing processing tasks to registered instances, resulting in swift performance.
What needs improvement?
There's room for improvement in how it handles data streaming capabilities. Our main challenge currently is that Matillion runs on an EC2 instance, limiting us to running only two processes simultaneously at the entry level. This constraint means we can run about sixteen jobs concurrently at the moment. However, once we transition to the SaaS offering, scalability will no longer be an issue. With the SaaS solution, we'll have the flexibility to run as many jobs as needed, making it a natural next step in our progression.
For how long have I used the solution?
I have been working with it for six years.
What do I think about the stability of the solution?
It exhibits a high level of stability and robustness. I would rate it nine out of ten.
What do I think about the scalability of the solution?
In our small business unit, we currently have around four users, with two of them utilizing Matillion within our organization. Considering our growing needs, we're contemplating transitioning to an enterprise SaaS solution where we would share the same instance. Currently, each user is billed individually, but consolidating to a shared instance seems more efficient. Scalability is excellent when using the SaaS solution, easily reaching a rating of ten out of ten. Each data pipeline request is encapsulated within a Docker container and spun off, allowing for instant scalability. Overall, I would rate it a nine out of ten in terms of performance and scalability.
How are customer service and support?
The technical support is excellent, and consistently helpful whenever we need assistance. We frequently engage with them, and the documentation is top-notch. Additionally, there's ample support available on YouTube covering various features. We heavily rely on their documentation site for guidance and reference. I would rate it eight out of ten.
How would you rate customer service and support?
Positive
Which solution did I use previously and why did I switch?
Previously, we relied on an on-premise solution, which often posed performance and capacity challenges due to server limitations. However, this approach involved upfront purchases and heavy licensing fees, which was a different model altogether. What I appreciate about Matillion is that it's available on the AWS Marketplace, allowing for easy installation and billing directly through our Amazon bill. This integration streamlines the process, as there's no need to manage separate vendor payments for ETL services.
What about the implementation team?
It seamlessly integrates with CodeConnect, which is the AWS Git repository, but it also supports integration with any Git repository, whether it's GitHub, GitLab, or another platform. Regardless of your choice of change control tool, Matillion can accommodate it. It simplifies the process by converting JSON payloads into a usable format, allowing for easy promotion from one environment to another. There's no maintenance required from our end; it's all handled automatically by the vendor. We receive weekly patches and periodic version updates, ensuring the solution stays up-to-date without any intervention from our side.
What's my experience with pricing, setup cost, and licensing?
We pay $5.40 per EC2 running hour, and we can reduce costs by stopping and starting the EC2 instances strategically. For instance, in our production environment, we run it for sixteen hours a day, while in our data environment, it's around ten to eleven hours a day, Monday to Friday. This approach allows us to save significantly on costs since we're billed per EC2 running hour. The absence of licensing commitments makes it easy to experiment with the tool, and if we decide it's not suitable, we can simply stop the ETL instance and cease incurring charges.
What other advice do I have?
Overall, I would rate it nine out of ten.
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)
Stable with excellent scalability
What is our primary use case?
My primary use case involves handling standard ETL tasks. I work on processing both our company's data and third-party data sources. While I focus on these standard ETL tasks, my colleagues excel in more advanced pipeline work.
What is most valuable?
The most valuable feature of Matillion ETL is its user-friendly graphical interface.
What needs improvement?
As someone new to the data industry and with limited experience in ETL tools, I'm not familiar with other options. My background was as a university professor until about a year ago, so I'm still getting acquainted with this field. I found some of the more complex aspects of ETL challenging, but I grasped the concepts fairly quickly.
For how long have I used the solution?
I have been using Matillion ETL for one year.
What do I think about the stability of the solution?
I would rate the stability a nine out of ten. It is quite stable.
What do I think about the scalability of the solution?
The scalability of the solution is excellent. I would give it a nine out of ten.
Matillion is our main ETL tool, and it is the one our consultants recommend. Currently, about 30 people at our company use it exclusively for all our ETL tasks.
What other advice do I have?
My advice to new users would be to start by going through the tutorials and working with example data. These tutorials are quite helpful in getting you familiar with the tool. Additionally, try working with data that you understand well, such as data from your previous work or a familiar dataset. This way, you can focus on learning how to use the tool without having to figure out complex data problems simultaneously. Overall, I would rate Matillion ETL a nine out of ten. It works very well.
Great for low code ELT solution
What do you like best about the product?
The users only need to know SQL to start working on Matillion, all the other technical things that demand other skill, Matillion got your back easily
What do you dislike about the product?
The poor documentation or examples about Query profiles. I think more examples to understan RSD file will be great to use it
What problems is the product solving and how is that benefiting you?
Integrate all customer datasource in a Data lake house with no code solution
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