CloverETL vs Pentaho Data Integration and Analytics comparison

Javlin and Hitachi Vantara are both solutions in the Data Integration category. Javlin is ranked #63, while Hitachi Vantara is ranked #24 with an average rating of 7.6. Javlin holds a 0.2% mindshare in DI, compared to Hitachi Vantara’s 1.5% mindshare. Additionally, 100% of Javlin users are willing to recommend the solution, compared to 94% of Hitachi Vantara users who would recommend it.

CloverETL

Read 2 CloverETL reviews

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203 Comparison Views

100% willing to recommend

Pentaho Data Integration an...

Read 52 Pentaho Data Integration and Analytics reviews

2,438 Views
1,080 Comparison Views

94% willing to recommend

CloverETL

Pentaho Data Integration an...

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Executive SummaryUpdated on Dec 19, 2024

Pentaho Data Integration and Analytics and CloverETL are competing in data integration and analytics. Pentaho has the upper hand in data processing capabilities, while CloverETL is known for scalability and efficient workflows.

Features: Pentaho Data Integration and Analytics is renowned for its comprehensive data integration tools, strong data transformation capabilities, and an extensive set of plugins. CloverETL is noted for advanced data transformation functionalities, robust performance in handling large data volumes, and superior scalability for large-scale data operations.

Ease of Deployment and Customer Service: Pentaho Data Integration offers a straightforward deployment process with considerable support documentation and community interaction. CloverETL provides a modular deployment structure with robust technical support, often requiring less initial configuration, allowing faster implementation.

Pricing and ROI: Pentaho's pricing structure is associated with a lower initial investment, delivering strong ROI through its wide range of features and supportive community. CloverETL, although requiring a higher initial setup cost, offers efficient resource allocation and outstanding scalability, resulting in significant long-term ROI.

To learn more, read our detailed CloverETL vs. Pentaho Data Integration and Analytics Report (Updated: November 2024).

Buyer's Guide

CloverETL vs. Pentaho Data Integration and Analytics

November 2024

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Categories and Ranking

CloverETL

Ranking in Data Integration

63rd

Average Rating

7.0

Reviews Sentiment

7.2

Number of Reviews

Ranking in other categories

Data Visualization (47th)

Pentaho Data Integration an...

Ranking in Data Integration

24th

Average Rating

8.0

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of December 2024, in the Data Integration category, the mindshare of CloverETL is 0.2%, up from 0.2% compared to the previous year. The mindshare of Pentaho Data Integration and Analytics is 1.5%, up from 0.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration

Featured Reviews

it_user854766

Vice President, Information and Technology Services at a tech services company with 11-50 employees

Provides wealth of pre-defined, customizable components, and descriptive logging for errors

* Familiar, intuitive GUI (Eclipse plug-in) coming from a Java development background. * In-depth, descriptive, and well-laid-out documentation. * Responsive support through forums, even directly from Clover staff. * Wealth of pre-defined components. * All components are customizable. * Descriptive logging, especially for error messages. * Ease of install/light footprint.

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Ryan Ferdon

Senior Data Engineer at Burgiss

Low-code makes development faster than with Python, but there were caching issues

If you're working with a larger data set, I'm not so sure it would be the best solution. The larger things got the slower it was. It was kind of buggy sometimes. And when we ran the flow, it didn't go from a perceived start to end, node by node. Everything kicked off at once. That meant there were times when it would get ahead of itself and a job would fail. That was not because the job was wrong, but because Pentaho decided to go at everything at once, and something would process before it was supposed to. There were nodes you could add to make sure that, before this node kicks off, all these others have processed, but it was a bit tedious. There were also caching issues, and we had to write code to clear the cache every time we opened the program, because the cache would fill up and it wouldn't run. I don't know how hard that would be for them to fix, or if it was fixed in version 10. Also, the UI is a bit outdated, but I'm more of a fan of function over how something looks. One other thing that would have helped with Pentaho was documentation and support on the internet: how to do things, how to set up. I think there are some sites on how to install it, and Pentaho does have a help repository, but it wasn't always the most useful.

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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

"Server features for scheduler: It is very easy to schedule jobs and monitor them. The interface is easy to use."

"Key features include wealth of pre-defined components; all components are customizable; descriptive logging, especially for error messages."

"Connectivity to various data sources: The ability to extract data from different data sources gives greater flexibility."

"No dependence on native language and ease of use."

"We use Lumada’s ability to develop and deploy data pipeline templates once and reuse them. This is very important. When the entire pipeline is automated, we do not have any issues in respect to deployment of code or with code working in one environment but not working in another environment. We have saved a lot of time and effort from that perspective because it is easy to build ETL pipelines."

"Lumada has allowed us to interact with our employees more effectively and compensate them properly. One of the cool things is that we use it to generate commissions for our salespeople and bonuses for our warehouse people. It allows us to get information out to them in a timely fashion. We can also see where they're at and how they're doing."

"The fact that it enables us to leverage metadata to automate data pipeline templates and reuse them is definitely one of the features that we like the best. The metadata injection is helpful because it reduces the need to create and maintain additional ETLs. If we didn't have that feature, we would have lots of duplicated ETLs that we would have to create and maintain. The data pipeline templates have definitely been helpful when looking at productivity and costs."

"Its drag-and-drop interface lets me and my team implement all the solutions that we need in our company very quickly. It's a very good tool for that."

"We also haven't had to create any custom Java code. Almost everywhere it's SQL, so it's done in the pipeline and the configuration. That means you can offload the work to people who, while they are not less experienced, are less technical when it comes to logic."

"I absolutely love Hitachi. I'm one of the forefront supporters of Hitachi for my firm. It's so easy to integrate within our environments. In terms of being able to quickly build ETL jobs, transform, and then automate them, it's really easy to integrate throughout for data analytics."

"One of the valuable features is the ability to use PL/SQL statements inside the data transformations and jobs."

"One of the most valuable features is the ability to create many API integrations. I'm always working with advertising agents and using Facebook and Instagram to do campaigns. We use Pentaho to get the results from these campaigns and to create dashboards to analyze the results."

More Pentaho Data Integration and Analytics pros

Cons

"Its documentation could be improved."

"Resource management: We typically run out of heap space, and even the allocation of high heap space does not seem to be enough."

"Needs: easier automated failure recovery; more, and more intuitive auto-generated/filled-in code for components; easier/more automated sync between CloverETL Designer and CloverETL Server."

"In terms of the flexibility to deploy in any environment, such as on-premise or in the cloud, we can do the cloud deployment only through virtual machines. We might also be able to work on different environments through Docker or Kubernetes, but we don't have an Azure app or an AWS app for easy deployment to the cloud. We can only do it through virtual machines, which is a problem, but we can manage it. We also work with Databricks because it works with Spark. We can work with clustered servers, and we can easily do the deployment in the cloud. With a right-click, we can deploy Databricks through the app on AWS or Azure cloud."

"It's not very stable, at least not in the case of the community edition. I'm working with the community edition right now and I think perhaps it is because of that it is not very stable, it causes the system to sometimes hang. I'm not sure if this is the case for pair tiers."

"Lumada could have more native connectors with other vendors, such as Google BigQuery, Microsoft OneDrive, Jira systems, and Facebook or Instagram. We would like to gather data from modern platforms using Lumada, which is a better approach. As a comparison, if you open Power BI to retrieve data, then you can get data from many vendors with cloud-native connectors, such as Azure, AWS, Google BigQuery, and Athena Redshift. Lumada should have more native connectors to help us and facilitate our job in gathering information from these new modern infrastructures and tools."

"The performance could be improved. If they could have analytics perform well on large volumes, that would be a big deal for our products."

"The testing and quality could really improve. Every time that there is a major release, we are very nervous about what is going to get broken. We have had a lot of experience with that, as even the latest one was broken. Some basic things get broken. That doesn't look good for Hitachi at all. If there is one place I would advise them to spend some money and do some effort, it is with the quality. It is not that hard to start putting in some unit tests so basic things don't get broken when they do a new release. That just looks horrible, especially for an organization like Hitachi."

"If you're working with a larger data set, I'm not so sure it would be the best solution. The larger things got the slower it was."

"One thing that I don't like, just a little, is the backward compatibility."

"I would like to see improvements made for real-time data processing."

More Pentaho Data Integration and Analytics cons

Pricing and Cost Advice

Information not available

"Sometimes we provide the licenses or the customer can procure their own licenses. Previously, we had an enterprise license. Currently, we are on a community license as this is adequate for our needs."

"I believe the pricing of the solution is more affordable than the competitors"

"You don't need the Enterprise Edition, you can go with the Community Edition. That way you can use it for free and, for free, it's a pretty good tool to use."

"The price of the regular version is not reasonable and it should be lower."

"The pricing has been pretty good. I'm used to using everything open-source or freeware-based. I understand that organizations need to make sure that the solutions are secure, and that's basically where I hit a roadblock in my current organization. They needed to ensure that we had a license and we had a secure way of accessing it so that no outside parties could get access to our data, but in terms of pricing, considering how much other teams are spending on cloud solutions or even their existing solutions, its price point is pretty good. At this time, there are no additional costs. We just have the licensing fees."

"I mostly used the open-source version. I didn't work with a license."

"The solution reduced our ETL development time by a lot because a whole project used to take about a month to get done previously. After having Lumada, it took just a week. For a big company in Brazil, it saves a team at least $10,000 a month."

"There is a good open source option (Community Edition)."

More Pentaho Data Integration and Analytics pricing and cost advice

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Top Industries

By visitors reading reviews

No data available

Financial Services Firm

23%

Computer Software Company

15%

Government

Comms Service Provider

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Questions from the Community

Ask a question

Earn 20 points

Which ETL tool would you recommend to populate data from OLTP to OLAP?

Hi Rajneesh, yes here is the feature comparison between the community and enterprise edition : https://www.hitachivantara.com/en-us/pdf/brochure/leverage-open-source-benefits-with-assurance-of-hita...

See all answers

What do you think can be improved with Hitachi Lumada Data Integrations?

In my opinion, the reporting side of this tool needs serious improvements. In my previous company, we worked with Hitachi Lumada Data Integration and while it does a good job for what it’s worth, ...

See all answers

What do you use Hitachi Lumada Data Integrations for most frequently?

My company has used this product to transform data from databases, CSV files, and flat files. It really does a good job. We were most satisfied with the results in terms of how many people could us...

See all answers

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Product Reports

Buyer's Guide

Data Integration

December 2024

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Buyer's Guide

Pentaho Data Integration and Analytics

December 2024

Pentaho Data Integration and Analytics report

Download Pentaho Data Integration and Analytics product report

Also Known As

No data available

Hitachi Lumada Data Integration, Kettle, Pentaho Data Integration

Learn More

Javlin

Hitachi Vantara

Overview

CloverETL is a rapid, end-to-end data integration solution. Businesses choose CloverETL for its usability and intuitive controls, along with its lightweight footprint, flexibility, and processing speed. Achieving true, rapid data integration means much more than just raw data processing power. Rapid refers to an end-to-end process that begins the moment a data-related problem is recognized to the point when the data is in the right place and form to be analyzed and monetized.

Pentaho Data Integration stands as a versatile platform designed to cater to the data integration and analytics needs of organizations, regardless of their size. This powerful solution is the go-to choice for businesses seeking to seamlessly integrate data from diverse sources, including databases, files, and applications. Pentaho Data Integration facilitates the essential tasks of cleaning and transforming data, ensuring it's primed for meaningful analysis. With a wide array of tools for data mining, machine learning, and statistical analysis, Pentaho Data Integration empowers organizations to glean valuable insights from their data. What sets Pentaho Data Integration apart is its maturity and a vibrant community of users and developers, making it a reliable and cost-effective option. Pentaho Data Integration offers a range of features, including a comprehensive ETL toolkit, data cleaning and transformation capabilities, robust data analysis tools, and seamless deployment options for data integration and analytics solutions, making it a go-to solution for organizations seeking to harness the power of their data.

Sample Customers

IBM, Oracle, MuleSoft, GoodData, Thomson Reuters, salesforce.com, Comcast, Active Network, SHOP.CA

66Controls, Providential Revenue Agency of Ro Negro, NOAA Information Systems, Swiss Real Estate Institute

Buyer's Guide

CloverETL vs. Pentaho Data Integration and Analytics

November 2024

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