Matillion Data Productivity Cloud with Maia: AI-Ready Data Integration

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.

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.

The main areas for improvement are AI features and scalability.

We have been using Matillion Data Productivity Cloud for the last five to six years.

The deployment process is easy.

Stability-wise, it is performing well.

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.

The support is good.

Positive

Previously we worked with Microsoft SSIS . SSIS  is an older technology, while Matillion Data Productivity Cloud is more advanced. Each solution has their own advantages and disadvantages.

We have experienced both time savings and money savings.

The pricing is managed by the tooling team. The pricing is moderate, neither expensive nor cheap.

We are working with JMeter  but not with other Apache products.

We cannot use open-source solutions due to compliance issues.

We work with AWS , 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.

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.

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.

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.

I have been working with Matillion Data Productivity Cloud for two years.

Matillion Data Productivity Cloud is stable and functions reliably as a product.

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.

Matillion's technical support is excellent. They communicate effectively and respond quickly to all inquiries.

The initial setup is straightforward. We completed the foundations process using Infrastructure as Code  (IaC ), which standardizes and simplifies the deployment process.

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.

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.

In many cases, clients consider buying a product from the same hyperscaler for an end-to-end solution, such as Microsoft Fabric .

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.

The solution is used for data ingestion from multiple sources to Snowflake and extract and load.

The solution's most valuable feature is the CDC (Change Data Capture) component.

Depending on the use case, the solution's pricing could be improved. Matillion ETL should include more enhanced capabilities for extracting data from the SAP systems.

I have been using Matillion ETL for more than one year.

Matillion ETL is a highly stable solution.

I rate the solution’s stability a nine out of ten.

Matillion ETL is a highly scalable solution because it is hosted on a cloud provider. So, that part is automatically taken care of. More than 100 users are using the solution in our organization.

I rate the solution’s scalability a nine out of ten.

The solution's technical support team is highly responsive.

Positive

Matillion ETL is a self-managed solution. Matillion deploys the tool. It's a SaaS offering that requires no extra deployment effort from our side. The solution can be deployed in a couple of minutes. Matillion's support team spun up the environment for us.

Since the solution is on the cloud and self-managed, your operational costs and admin efforts will decrease. The solution has saved around 15% to 20% of our operational costs.

The solution's pricing is not based on the licensing cost but on the running hours when the Matillion instance is up and running. Its pricing model is different from the traditional pricing models of Talend or Informatica. The solution was not expensive for my use case.

I rate the solution’s pricing an eight out of ten.

The solution's orchestration capabilities are pretty good. It does have an integration with DBT. I would recommend the solution to other users because it has a very clear roadmap with a good support system. The solution’s maintenance is done through an in-house team of three to four engineers.

Overall, I rate the solution an eight out of ten.

In a project where we migrated from on-prem solutions to the cloud, we used Matillion and Snowflake, which streamlined the process significantly.

Matillion ETL's ability to conduct end-to-end data migration is valuable. We can create jobs, monitor them, and manage workflows effectively.

The product's scalability needs improvement. Perhaps adding more connectors would be beneficial.

The product is quite stable and can handle complex data integration tasks well.

I rate the platform scalability around six or seven. Depending on the specific architecture, parallel processing needs, and data types involved, it could be optimized.

I haven't contacted the technical support team, but the online documentation and community resources are quite sufficient.

A team of two to three ETL architects and data engineers is required to work on deployment. 

We can monitor and manage real-time data pipelines, analyze task logs, and automate data pipelines wherever possible. We also apply parameterization to improve efficiency using the product.

It adapts well to changing data volumes and types. I would recommend it, especially for cloud data integration.

I rate it a seven or eight. 

I am not specifically into ETL or data pipelines only since I am basically a data architect who is more into designing cloud-based data solutions. My focus is more on understanding the user's use cases and then designing a solution.

When it comes to Snowflake and Matillion ETL, both offer a lot of compatibility and ease of use. The improvement area could be possible if the tool provides better integration capabilities with other ecosystems, including governance tools or data cataloging tools, as it is currently an area where the solution is lacking.

I have been using Matillion ETL for fifteen years.

Matillion ETL runs the codes in Snowflake, which itself is a highly scalable product, and ultimately provides greater scalability due to the combination of both the products.

I did not contact the solution's technical support team because, most of the time, our company could resolve the issues related to the product with the information available online.

I am not able to recall the products that I have used in the past and be able to make a comparison between those tools against Matillion ETL. I have used Fivetran and DBT tools at some point in time, but I am not able to record when I use them. I know that despite using some other products in the past, my company ended up choosing and recommending Matillion ETL since its features did fit into the requirements of my organization.

The product's initial setup phase was easy. Matillion ETL is readily available from Snowflake's marketplace.

Matillion ETL and DBT help our company by making it easy for us to build data pipelines, particularly when Snowflake was used as a data platform.

Matillion ETL helps my company automate the data pipeline and allows us to optimize data workflows.

In the context of the cloud-based data platforms, the good aspect of Matillion ETL stems from the fact that it actually runs code in the platform, which is basically like a push-down approach wherein, though our company builds the pipeline using the tool, the actual execution of those pipelines happens within Snowflake.

The product supports our company's growing data needs.

The product is integrated with Snowflake. Through a straightforward process, Matillion ETL can be degraded with Snowflake.

The integration capabilities of the tool improved our company's overall data analytics pipeline.

I am satisfied with the product interface.

The product has had an impact on my company's team productivity. It is an easy-to-use tool with a simple UI and serves as a no-code ETL solution.

I recommend the tool to those who specifically use Snowflake in their companies.

I rate the tool an eight out of ten.