CloverDX Designer vs Matillion Data Productivity Cloud comparison

The compared CloverDX and Matillion solutions aren't in the same category. CloverDX is ranked #74 in DI , and holds a 0.1% mindshare in the category. Matillion is ranked #8 in CDI , with an average rating of 8.1, and holds a 3.3% mindshare. Additionally, 100% of CloverDX users are willing to recommend the solution, compared to 92% of Matillion users who would recommend it.

CloverDX Designer

Read 1 CloverDX Designer review

136 Views
70 Comparison Views

100% willing to recommend

Matillion Data Productivity...

Read 27 Matillion Data Productivity Cloud reviews

1,343 Views
398 Comparison Views

92% willing to recommend

CloverDX Designer

Matillion Data Productivity...

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Executive SummaryUpdated on Mar 31, 2025

Matillion Data Productivity Cloud and CloverDX Designer compete in the data management and integration space. While Matillion is more favorable in pricing and support, CloverDX Designer's robust features make it a compelling choice for data-centric organizations.

Features: Matillion Data Productivity Cloud's cloud-native architecture supports various environments, ensuring seamless integration and real-time data transformation. Its scalability addresses growing business needs, enhancing appeal for expanding businesses. CloverDX Designer offers exceptional customization capabilities and complex data transformation support, allowing extensive control over data workflows. This advanced data manipulation gives CloverDX an edge for businesses with complex needs.

Ease of Deployment and Customer Service: Matillion's quick, straightforward deployment in cloud settings is complemented by responsive customer service. In contrast, CloverDX provides detailed deployment options that accommodate different infrastructures but can involve intricate setup. However, CloverDX's robust customer support assists in addressing challenges, with adaptable deployment methods offering versatility despite added complexity.

Pricing and ROI: Matillion is cost-effective with pricing models adapting to business scales, promising a quicker ROI. CloverDX, while potentially higher in initial setup costs, is seen as valuable for complex data handling, with ROI realized through powerful transformation capabilities. Matillion appeals to budget-conscious organizations, while CloverDX justifies its cost with advanced functionality.

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Buyer's Guide

Data Integration

June 2025

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Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Categories and Ranking

CloverDX Designer

Average Rating

7.0

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

Data Integration (74th)

Matillion Data Productivity...

Average Rating

8.4

Reviews Sentiment

7.4

Number of Reviews

Ranking in other categories

Cloud Data Integration (8th)

Mindshare comparison

While both are Data Integration and Access solutions, they serve different purposes. CloverDX Designer is designed for Data Integration and holds a mindshare of 0.1%, up 0.1% compared to last year.
Matillion Data Productivity Cloud, on the other hand, focuses on Cloud Data Integration, holds 3.3% mindshare, down 4.5% since last year.

Data Integration

Cloud Data Integration

Featured Reviews

reviewer1518951

Data professional at a financial services firm with 1,001-5,000 employees

Simple, stable, and allows us to handle data from various sources, but needs enterprise features for logging, recoverability, and monitoring

If I could give any advice to the guys who are developing it, I would suggest them to really look at the enterprise features, such as being able to log what's going on, being able to capture the current state of processing, and being able to recover from error situations. So, there should be a focus on logging, recoverability, and monitoring. We should be able to monitor what's going on, and in case of any issues, we should be able to recover and restart processing and other things. For scalability and performance, I would probably suggest the Pushdown feature so that you can do the transformation directly on the data source. You do not need to do that calculation within the ETL server. For this, you should be aware of the type of data because each database or kind of storage, such as Hadoop, has its own ANSI standard or language, such as SQL. Microsoft, Oracle, and IBM have their own language. Based on the feedback that I have got, its initial setup takes some time. It could perhaps be simpler.

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Tomáš Hronek

Data Engineer at Merck

Used for wrangling or transforming data from sources like S3 and Databricks

I use Matillion ETL for wrangling or transforming data from sources like S3 and Databricks The most valuable feature of Matillion ETL is the UI experience in which you can drag and drop most of the transformation. Sometimes, we have issues with the solution's stability and need to restart it for…

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Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"Its simplicity and the way it handles graphs are the most valuable features."

"It is pretty user-friendly, even for people who aren't super technical."

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

"The product has a good user interface."

"It has good integrations with Amazon Redshift and other AWS services."

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

"The most valuable feature of Matillion ETL is its ease of use. If you have had some experience with other solutions, such as Snowflake, the use of this solution will be simple."

"Matillion's technical support is excellent."

"It's been able to do everything we require."

More Matillion Data Productivity Cloud pros

Cons

"If I could give any advice to the guys who are developing it, I would suggest them to really look at the enterprise features, such as being able to log what's going on, being able to capture the current state of processing, and being able to recover from error situations. So, there should be a focus on logging, recoverability, and monitoring. We should be able to monitor what's going on, and in case of any issues, we should be able to recover and restart processing and other things. For scalability and performance, I would probably suggest the Pushdown feature so that you can do the transformation directly on the data source. You do not need to do that calculation within the ETL server. For this, you should be aware of the type of data because each database or kind of storage, such as Hadoop, has its own ANSI standard or language, such as SQL. Microsoft, Oracle, and IBM have their own language. Based on the feedback that I have got, its initial setup takes some time. It could perhaps be simpler."

"Unlike Snowflake which automatically takes care of upgrading to the latest version and includes additional features, with Matillion ETL we need to do this ourselves."

"While the UI is good, it could be improved in its efficiency and made easier to use."

"When using the SQL loader type there were not a lot of pre-processing features for the data. For example, if there is a table with twenty columns, but we only want to load ten columns. In that case, we can use a security script to select the specific columns needed. However, if we want to perform extensive pre-processing of the data, I faced some challenges with Matillion ETL. I did not encounter many challenges, but my overall experience is limited as I only have three years of experience."

"In the next release, we would like to have connections to more databases."

"Matillion ETL should include more enhanced capabilities for extracting data from the SAP systems."

"The current version is a bit more limited because it's on a virtual machine, and everything executes on that one virtual machine."

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

"Sometimes, we have issues with the solution's stability and need to restart it for three weeks or more."

More Matillion Data Productivity Cloud cons

Pricing and Cost Advice

"Its price and value for money would be okay for our purpose if there were some additional features."

"Its price depends on what you expect. You pay on a monthly basis, but there is a possibility to have special contracts depending on the installation."

"It is cost-effective. Based on our use case, it's efficient and cheap. It saves a lot of money and our upfront costs are less."

"The AWS pricing and licensing are a cost-effective solution for data integration needs."

"I think it is cost conscious. It used to be very cheap and they have more recently bumped up the pricing, so it is competitive now."

"The price of Matillion ETL is reasonable."

"The product must improve its pricing."

"The pricing depends on what edition the customer opts for. 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."

"Matillion ETL has a pay-as-you-go pricing model of a few dollars per hour of runtime."

More Matillion Data Productivity Cloud pricing and cost advice

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Top Industries

By visitors reading reviews

No data available

Financial Services Firm

19%

Computer Software Company

15%

Manufacturing Company

Healthcare Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Questions from the Community

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What do you like most about Matillion ETL?

The new version with the Productivity Cloud is very simple. It's easy to use, navigate, and understand.

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What is your experience regarding pricing and costs for Matillion ETL?

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 c...

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What needs improvement with Matillion ETL?

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 raise...

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Comparisons

SSIS vs CloverDX Designer

Compared 100% of the time

More CloverDX Designer Competitors

Azure Data Factory vs Matillion Data Productivity Cloud

Compared 13% of the time

AWS Glue vs Matillion Data Productivity Cloud

Compared 10% of the time

SSIS vs Matillion Data Productivity Cloud

Compared 9% of the time

Oracle Data Integrator (ODI) vs Matillion Data Productivity Cloud

Compared 6% of the time

SnapLogic vs Matillion Data Productivity Cloud

Compared 5% of the time

More Matillion Data Productivity Cloud Competitors

Product Reports

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Data Integration

June 2025

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Buyer's Guide

Matillion Data Productivity Cloud

May 2025

Matillion Data Productivity Cloud report

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Also Known As

No data available

Matillion ETL for Redshift, Matillion ETL for Snowflake, Matillion ETL for BigQuery

Overview

We help clients build and manage better data pipelines, with the CloverDX Data Management Platform and our in-house team of data experts.

Founded in 2007, we now have offices in the US, UK and Czech Republic, and work with some of the world’s leading companies in industries such as finance, healthcare and consulting.

CloverDX

Matillion Data Productivity Cloud features an intuitive graphical interface, seamless AWS integration, and efficient data management. Its tools streamline complex tasks for SFDC, RDS, Marketo, Facebook, and Google AdWords.

Matillion Data Productivity Cloud provides fast transformations with built-in verification, easy scheduling, and sampling. With automatic scalability and diverse data source support, it simplifies complex data tasks. Users benefit from cloud data warehousing and integrating data into Snowflake while appreciating its ease of use by non-technical teams. Enhancements can focus on frequent API adjustments, improved documentation, faster performance with less latency, and better error handling.

What are the key features of Matillion Data Productivity Cloud?

User-Friendly Interface: Simplifies interaction for non-technical users with a graphical interface.
Seamless Integration: Works smoothly with AWS, SFDC, RDS, Marketo, Facebook, and Google AdWords.
Automatic Scalability: Efficiently manages varying workloads with scale-up and down capabilities.
Efficient Data Handling: Streamlines transformations, scheduling, and sample data verifications.
Diverse Data Source Support: Easily integrates multiple data sources for streamlined processes.

What benefits and ROI should users seek in reviews?

Ease of Use: Reduces complexity for non-technical teams with intuitive operation.
Performance Efficiency: Fast data processing and transformations enhance productivity.
Cloud Compatibility: Supports integration with cloud platforms for versatile data solutions.
Time-Saving Scheduling: Automates data tasks, allowing users to focus on other priorities.
Scalability: Automatically adjusts to workload needs, optimizing resource use and cost.

In industries such as technology, finance, and healthcare, Matillion Data Productivity Cloud is implemented to streamline ETL processes, optimize data pipeline construction, and enhance data migration efforts. It supports efficient data loading and integration between cloud and on-premises databases, aiding industries in managing data-driven projects.

Matillion

Sample Customers

Allant Group, NDP, Porch, GoodData

Thrive Market, MarketBot, PWC, Axtria, Field Nation, GE, Superdry, Quantcast, Lightbox, EDF Energy, Finn Air, IPRO, Twist, Penn National Gaming Inc

Find out what your peers are saying about Microsoft, Informatica, Talend and others in Data Integration. Updated: June 2025.

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