Matillion ETL vs Spring Cloud Data Flow comparison

The compared Matillion and VMware solutions aren't in the same category. Matillion is ranked #5 in CDI , with an average rating of 8.4, and holds a 4.4% mindshare in the category. VMware is ranked #22 in DI , with an average rating of 7.6, and holds a 1.1% mindshare. Additionally, 96% of Matillion users are willing to recommend the solution, compared to 88% of VMware users who would recommend it.

Matillion ETL

Read 26 Matillion ETL reviews

2,234 Views
1,536 Comparison Views

96% willing to recommend

Spring Cloud Data Flow

Read 9 Spring Cloud Data Flow reviews

1,829 Views
1,384 Comparison Views

88% willing to recommend

Matillion ETL

Spring Cloud Data Flow

Comparison Buyer's Guide

Download the report

Executive Summary

We performed a comparison between Matillion ETL and Spring Cloud Data Flow based on real PeerSpot user reviews.

Find out in this report how the two Cloud Data Integration solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed Matillion ETL vs. Spring Cloud Data Flow Report (Updated: August 2022).

Buyer's Guide

Matillion ETL vs. Spring Cloud Data Flow

August 2022

Download the complete report

Helped 815,854 peers since 2012

Categories and Ranking

Matillion ETL

Average Rating

8.4

Number of Reviews

Ranking in other categories

Cloud Data Integration (5th)

Spring Cloud Data Flow

Average Rating

7.8

Number of Reviews

Ranking in other categories

Data Integration (22nd), Streaming Analytics (10th)

Mindshare comparison

While both are Data Integration and Access solutions, they serve different purposes. Matillion ETL is designed for Cloud Data Integration and holds a mindshare of 4.4%, down 6.0% compared to last year.
Spring Cloud Data Flow, on the other hand, focuses on Data Integration, holds 1.1% mindshare, up 1.0% since last year.

Cloud Data Integration

Data Integration

Featured Reviews

AntonHaupt

Data Architect at Capitec

Jan 23, 2024

Efficient data integration and transformation with seamless cloud-native integration

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.

Read full review

NitinGoyal

Engineering Lead at Naukri.com

Aug 15, 2024

Has a plug-and-play model and provides good robustness and scalability

The solution's community support could be improved. I don't know why the Spring Cloud Data Flow community is not very strong. Community support is very limited whenever you face any problem or are stuck somewhere. I'm not sure whether it has improved in the last six months because this pipeline was set up almost two years ago. I struggled with that a lot. For example, there was limited support whenever I got an exception and sought help from Stack Overflow or different forums. Interacting with Kubernetes needs a few certificates. You need to define all the certificates within your application. With the help of those certificates, your Java application or Spring Cloud Data Flow can interact with Kubernetes. I faced a lot of hurdles while placing those certificates. Despite following the official documentation to define all the replicas, readiness, and liveliness probes within the Spring Cloud Data Flow application, it was not working. So, I had to troubleshoot while digging in and debugging the internals of Spring Cloud Data Flow at that time. It was just a configuration mismatch, and I was doing nothing weird. There was a small spelling difference between how Spring Cloud Data Flow was expecting it and how I passed it. I was just following the official documentation.

Read full review

Quotes from Members

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

Pros

"It has helped us to get onto the cloud quickly."

"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."

"The technical support treats us well. They already have a support portal, and they are responsive, which helps."

"It can scale to a great extent. It can handle the load that we are putting on it, which is about 5TBs."

"The simplicity of this tool is nice. It has a good graphical user interface. You can also do a lot of generic stuff in the tool. If there is good connectivity to a cloud database, such as Snowflake, and you can have a lot of Snowflake functionality in the tool."

"The most valuable feature of Matillion ETL is the ETL. The solution is open-source which provides advantages, such as good performance and high efficiency. Additionally, it supports three data types which eliminates predefining the data, and we can write script models in Python."

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

"We allow non-technical people to use Matillion to load data into our data warehouse for reporting. Thus, it is easy enough to use that we don't always have to get a technical person involved in setting up a data movement (ETL)."

More Matillion ETL pros

"There are a lot of options in Spring Cloud. It's flexible in terms of how we can use it. It's a full infrastructure."

"The most valuable features of Spring Cloud Data Flow are the simple programming model, integration, dependency Injection, and ability to do any injection. Additionally, auto-configuration is another important feature because we don't have to configure the database and or set up the boilerplate in the database in every project. The composability is good, we can create small workloads and compose them in any way we like."

"The dashboards in Spring Cloud Dataflow are quite valuable."

"The solution's most valuable feature is that it allows us to use different batch data sources, retrieve the data, and then do the data processing, after which we can convert and store it in the target."

"The ease of deployment on Kubernetes, the seamless integration for orchestration of various pipelines, and the visual dashboard that simplifies operations even for non-specialists such as quality analysts."

"The product is very user-friendly."

"The most valuable feature is real-time streaming."

"The best thing I like about Spring Cloud Data Flow is its plug-and-play model."

Cons

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

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

"Performance can be improved for efficiency, and it can be made faster."

"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."

"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."

"I am looking forward to seeing the expansion of the source range for their data loader product."

"It can have multi-environment support. We should be able to deploy it in different environments. Its integration with SAP connection is not so nice, which should be improved. It can also support an on-prem database."

"Going forward, I would like them to add custom jobs, since we still have to run these outside of Matillion."

More Matillion ETL cons

"Spring Cloud Data Flow is not an easy-to-use tool, so improvements are required."

"The configurations could be better. Some configurations are a little bit time-consuming in terms of trying to understand using the Spring Cloud documentation."

"Spring Cloud Data Flow could improve the user interface. We can drag and drop in the application for the configuration and settings, and deploy it right from the UI, without having to run a CI/CD pipeline. However, that does not work with Kubernetes, it only works when we are working with jars as the Spring Cloud Data Flow applications."

"I would improve the dashboard features as they are not very user-friendly."

"There were instances of deployment pipelines getting stuck, and the dashboard not always accurately showing the application status, requiring manual intervention such as rerunning applications or refreshing the dashboard."

"The solution's community support could be improved."

"On the tool's online discussion forums, you may get stuck with an issue, making it an area where improvements are required."

"Some of the features, like the monitoring tools, are not very mature and are still evolving."

Pricing and Cost Advice

"The solution's pricing is not based on the licensing cost but on the running hours when the Matillion instance is up and running."

"The prices needs to be lower."

"I have heard from my manager and other higher ups, "This product is cheaper than other things on the market," and they have done the research."

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

"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."

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

"A rough estimation of the cost is around 20,000 dollars a month, however, this is dependent on the machine used and how Matillion ETL is used."

"Matillion ETL is expensive."

More Matillion ETL pricing and cost advice

"If you want support from Spring Cloud Data Flow there is a fee. The Spring Framework is open-source and this is a free solution."

"The solution provides value for money, and we are currently using its community edition."

"This is an open-source product that can be used free of charge."

See which vendors are best for you

Use our free recommendation engine to learn which Cloud Data Integration solutions are best for your needs.

See recommendations

815,854 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

16%

Computer Software Company

14%

Manufacturing Company

Government

Financial Services Firm

29%

Computer Software Company

17%

Manufacturing Company

Retailer

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

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.

See all answers

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

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 ...

See all answers

What needs improvement with Matillion ETL?

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.

See all answers

What needs improvement with Spring Cloud Data Flow?

I would improve the dashboard features as they are not very user-friendly. Another area for improvement is the documentation, as it is not very precise. There are limited resources available on Spr...

See all answers

What is your primary use case for Spring Cloud Data Flow?

I am a developer using Spring Cloud Dataflow. We primarily use it to convert our applications from monolithic to microservices. The solution is used for scheduling tasks in a specific order and ens...

See all answers

What advice do you have for others considering Spring Cloud Data Flow?

My advice would be to thoroughly review the documentation and understand if Spring Cloud Dataflow is the right solution for your application. For applications with only one or two microservices, it...

See all answers

Comparisons

Azure Data Factory vs Matillion ETL

Compared 13% of the time

SSIS vs Matillion ETL

Compared 9% of the time

AWS Glue vs Matillion ETL

Compared 9% of the time

Snowflake vs Matillion ETL

Compared 8% of the time

Informatica PowerCenter vs Matillion ETL

Compared 7% of the time

More Matillion ETL Competitors

Apache Flink vs Spring Cloud Data Flow

Compared 33% of the time

TIBCO BusinessWorks vs Spring Cloud Data Flow

Compared 10% of the time

Google Cloud Dataflow vs Spring Cloud Data Flow

Compared 9% of the time

Apache Spark Streaming vs Spring Cloud Data Flow

Compared 7% of the time

Azure Data Factory vs Spring Cloud Data Flow

Compared 5% of the time

More Spring Cloud Data Flow Competitors

Product Reports

Buyer's Guide

Matillion ETL

November 2024

Download Matillion ETL product report

Buyer's Guide

Spring Cloud Data Flow

October 2024

Download Spring Cloud Data Flow product report

Also Known As

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

No data available

Learn More

Matillion

VMware

Overview

Matillion ETL is a powerful tool for extracting, transforming, and loading large amounts of data from various sources into cloud data warehouses like Snowflake. Its ability to load data dynamically and efficiently using metadata is a standout feature, as is its open-source ETL with good performance and high efficiency.

The solution has a graphical interface for jobs, is easily adjustable and extensible, and allows for scheduling and error reporting. Matillion ETL has helped organizations move to a cloud-based solution, bridge the gap between on-premises and on-cloud, and perform complex migration projects.

Spring Cloud Data Flow is a toolkit for building data integration and real-time data processing pipelines.
Pipelines consist of Spring Boot apps, built using the Spring Cloud Stream or Spring Cloud Task microservice frameworks. This makes Spring Cloud Data Flow suitable for a range of data processing use cases, from import/export to event streaming and predictive analytics. Use Spring Cloud Data Flow to connect your Enterprise to the Internet of Anything—mobile devices, sensors, wearables, automobiles, and more.

Sample Customers

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

Information Not Available

Buyer's Guide

Matillion ETL vs. Spring Cloud Data Flow

August 2022

Free Report: Matillion ETL vs. Spring Cloud Data Flow

Find out what your peers are saying about Matillion ETL vs. Spring Cloud Data Flow and other solutions. Updated: August 2022.

DOWNLOAD NOW

815,854 professionals have used our research since 2012.

See our Matillion ETL vs. Spring Cloud Data Flow report.

We monitor all Cloud Data Integration reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.