Apache Spark vs Pentaho Business Analytics comparison

The compared Apache and Hitachi Vantara solutions aren't in the same category. Apache is ranked #1 in H , with an average rating of 8.6, and holds a 17.8% mindshare in the category. Hitachi Vantara is ranked #21 in BIT , with an average rating of 8.5, and holds a 0.4% mindshare. Additionally, 90% of Apache users are willing to recommend the solution, compared to 89% of Hitachi Vantara users who would recommend it.

Apache Spark

Read 65 Apache Spark reviews

1,580 Views
1,196 Comparison Views

90% willing to recommend

Pentaho Business Analytics

Read 43 Pentaho Business Analytics reviews

617 Views
455 Comparison Views

89% willing to recommend

Apache Spark

Pentaho Business Analytics

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Executive Summary

We performed a comparison between Apache Spark and Pentaho Business Analytics based on real PeerSpot user reviews.

Find out what your peers are saying about Apache, Cloudera, Amazon Web Services (AWS) and others in Hadoop.

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February 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

Apache Spark

Average Rating

8.4

Reviews Sentiment

7.7

Number of Reviews

Ranking in other categories

Hadoop (1st), Compute Service (4th), Java Frameworks (2nd)

Pentaho Business Analytics

Average Rating

8.0

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

BI (Business Intelligence) Tools (21st), Cloud Operations Analytics (4th), Reporting (16th)

Mindshare comparison

Apache Spark and Pentaho Business Analytics aren’t in the same category and serve different purposes. Apache Spark is designed for Hadoop and holds a mindshare of 17.8%, down 21.2% compared to last year.
Pentaho Business Analytics, on the other hand, focuses on BI (Business Intelligence) Tools, holds 0.4% mindshare, down 0.6% since last year.

Hadoop

BI (Business Intelligence) Tools

Featured Reviews

Ilya Afanasyev

Senior Software Development Engineer at Yahoo!

Reliable, able to expand, and handle large amounts of data well

We use batch processing. It works well with our formats and file versions. There's a lot of functionality. In our pipeline each hour, we make a copy of data from MongoDB, of the changes from MongoDB to some specific file. Each time pipeline copied all of the data, it would do it each time without changes to all of the tables. Tables have a lot of data, and in the last MongoDB version, there is a possibility to read only changed data. This reduced the cost and configuration of the cluster, and we saved about $150,000. The solution is scalable. It's a stable product.

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Sayan König

Senior Manager, Financial Services at KPMG

Flexible, easy to understand, and simple to set up

The repository should be improved. There should be the possibility to have versioning, to make it combinable with some Git repositories or something like that, to check out the processes and make sure it has a traceable history. The solution could really be improved. There are too many bugs in our version.

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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

"I found the solution stable. We haven't had any problems with it."

"The tool's most valuable feature is its speed and efficiency. It's much faster than other tools and excels in parallel data processing. Unlike tools like Python or JavaScript, which may struggle with parallel processing, it allows us to handle large volumes of data with more power easily."

"Spark is used for transformations from large volumes of data, and it is usefully distributed."

"The most significant advantage of Spark 3.0 is its support for DataFrame UDF Pandas UDF features."

"The most valuable feature is the Fault Tolerance and easy binding with other processes like Machine Learning, graph analytics."

"Features include machine learning, real time streaming, and data processing."

"With Hadoop-related technologies, we can distribute the workload with multiple commodity hardware."

"One of the key features is that Apache Spark is a distributed computing framework. You can help multiple slaves and distribute the workload between them."

More Apache Spark pros

"Pentaho Business Analytics' best features include the ease of developing data flows and the wide range of options to connect to databases, including those on the cloud."

"Easy to use components to create the job."

"It is robust, offers market intelligence, and utilizes modules effectively."

"The most valuable feature of Pentaho is the Tableau report."

"Pentaho is an analytics platform that can be used when an organization has a lot of big data storage systems already installed and needs to manage and analyze that data. It has a specific use case for unstructured data, such as documents, and needs to be able to search and analyze it."

"The initial setup is pretty straightforward."

"I use the BI Server, CDE Dashboards, Saiku, and Kettle, because these tools are very good and highly experienced."

"We were able to install it without any assistance from tech support."

Cons

"I know there is always discussion about which language to write applications in and some people do love Scala. However, I don't like it."

"Apache Spark could improve the connectors that it supports. There are a lot of open-source databases in the market. For example, cloud databases, such as Redshift, Snowflake, and Synapse. Apache Spark should have connectors present to connect to these databases. There are a lot of workarounds required to connect to those databases, but it should have inbuilt connectors."

"We've had problems using a Python process to try to access something in a large volume of data. It crashes if somebody gives me the wrong code because it cannot handle a large volume of data."

"More ML based algorithms should be added to it, to make it algorithmic-rich for developers."

"They could improve the issues related to programming language for the platform."

"There were some problems related to the product's compatibility with a few Python libraries."

"If you have a Spark session in the background, sometimes it's very hard to kill these sessions because of D allocation."

"The logging for the observability platform could be better."

More Apache Spark cons

"The tool is very good, and yet it has some problems as it relies heavily on Java."

"Pentaho Business Analytics' user interface is outdated."

"Another concern is that Pentaho is not customizable or interactive."

"Logging capability is needed."

"We did not achieve the ROI. The work delivered to users had lesser value than the subscription cost."

"Version control would be a good addition."

"Deployment is not simple. It is not simple because we are dealing with a lot of data; we are dealing with a lot of storage. So, it's not a simple process."

"Pentaho, at the general level, should greatly improve the easy construction of its dashboards and easy integration of information from different sources without technical user intervention."

More Pentaho Business Analytics cons

Pricing and Cost Advice

"They provide an open-source license for the on-premise version."

"It is quite expensive. In fact, it accounts for almost 50% of the cost of our entire project."

"We are using the free version of the solution."

"On the cloud model can be expensive as it requires substantial resources for implementation, covering on-premises hardware, memory, and licensing."

"Licensing costs can vary. For instance, when purchasing a virtual machine, you're asked if you want to take advantage of the hybrid benefit or if you prefer the license costs to be included upfront by the cloud service provider, such as Azure. If you choose the hybrid benefit, it indicates you already possess a license for the operating system and wish to avoid additional charges for that specific VM in Azure. This approach allows for a reduction in licensing costs, charging only for the service and associated resources."

"It is an open-source solution, it is free of charge."

"Apache Spark is open-source. You have to pay only when you use any bundled product, such as Cloudera."

"Apache Spark is an open-source tool."

More Apache Spark pricing and cost advice

"Free and commercial versions are available."

"Pentaho is expensive ."

"We were lucky enough to find a Pentaho OEM partner who offered a data warehouse model and the ETL software for about 60K SGD per year."

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Comparison Review

it_user6978

Co-Founder at Helical IT Solution (Jaspersoft, Pentaho, Talend, Kettle, DWBI, ETL, Ctools, iReport, Jasper Report)

Jun 10, 2013

Jaspersoft vs. Pentaho – Which one to use & is there any need to purchase the commercial edition

Any company (be it technology, manfucaturing, human resource, ecommerce, SME etc) always has the need for Business Intelligence to some or the other extent. If cost is one of the consideration factor, then the 2 BI tools which are at the forefront are Pentaho and Jaspersoft. But, often the same…

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Top Industries

By visitors reading reviews

Financial Services Firm

28%

Computer Software Company

13%

Manufacturing Company

Comms Service Provider

Financial Services Firm

27%

Computer Software Company

13%

Government

Educational Organization

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

What do you like most about Apache Spark?

We use Spark to process data from different data sources.

See all answers

What is your experience regarding pricing and costs for Apache Spark?

Compared to other solutions like Doc DB, Spark is more costly due to the need for extensive infrastructure. It requires significant investment in infrastructure, which can be expensive. While cloud...

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What needs improvement with Apache Spark?

The Spark solution could improve in scheduling tasks and managing dependencies. Spark alone cannot handle sequential tasks, requiring environments like Airflow scheduler or scripts. For instance, o...

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Seeking lightweight open source BI software

There are many...It would rather depend what System BI architecture or Enterprise legacy you have at your end...I would recommend as follows: 1) If you have legacies of SAP, Oracle - look for SAP...

See all answers

What is your experience regarding pricing and costs for Pentaho Business Analytics?

For those starting to use this tool, there is a free version available which is beneficial. The company also finds the pricing to be good.

See all answers

What needs improvement with Pentaho Business Analytics?

The tool is very good, and yet it has some problems as it relies heavily on Java. The platform works with Java, and it has brought some issues to the company.

See all answers

Comparisons

Spring Boot vs Apache Spark

Compared 27% of the time

SAP HANA vs Apache Spark

Compared 12% of the time

AWS Batch vs Apache Spark

Compared 12% of the time

Cloudera Distribution for Hadoop vs Apache Spark

Compared 8% of the time

Spark SQL vs Apache Spark

Compared 7% of the time

More Apache Spark Competitors

KNIME vs Pentaho Business Analytics

Compared 32% of the time

Databricks vs Pentaho Business Analytics

Compared 19% of the time

Microsoft Power BI vs Pentaho Business Analytics

Compared 15% of the time

SAP Crystal Reports vs Pentaho Business Analytics

Compared 9% of the time

Microsoft SQL Server Reporting Services vs Pentaho Business Analytics

Compared 5% of the time

More Pentaho Business Analytics Competitors

Product Reports

Buyer's Guide

Apache Spark

March 2025

Download Apache Spark product report

Buyer's Guide

Pentaho Business Analytics

March 2025

Download Pentaho Business Analytics product report

Also Known As

No data available

Pentaho, Kettle, Hitachi Pentaho Business Analytics

Overview

Spark provides programmers with an application programming interface centered on a data structure called the resilient distributed dataset (RDD), a read-only multiset of data items distributed over a cluster of machines, that is maintained in a fault-tolerant way. It was developed in response to limitations in the MapReduce cluster computing paradigm, which forces a particular linear dataflowstructure on distributed programs: MapReduce programs read input data from disk, map a function across the data, reduce the results of the map, and store reduction results on disk. Spark's RDDs function as a working set for distributed programs that offers a (deliberately) restricted form of distributed shared memory

Apache

Pentaho is an open source business intelligence company that provides a wide range of tools to help their customers better manage their businesses. These tools include data integration software, mining tools, dashboard applications, online analytical processing options, and more.

Pentaho has two product categories: There is the standard enterprise version. This is the product that comes directly from Pentaho itself with all of the benefits, features, and programs that come along with a paid application such us analysis services, dashboard design, and interactive reporting.

The alternative is an open source version, which the public is permitted to add to and tweak the product. This solution has its advantages, aside from the fact that it is free, in that there are many more people working on the project to improve its quality and breadth of functionality.

Hitachi Vantara

Sample Customers

NASA JPL, UC Berkeley AMPLab, Amazon, eBay, Yahoo!, UC Santa Cruz, TripAdvisor, Taboola, Agile Lab, Art.com, Baidu, Alibaba Taobao, EURECOM, Hitachi Solutions

Cargo 2000 Lufthansa, Marketo, ModCloth, Cardiac Science, Telefonica, ExactTarget, Active Broadband Networks, and Brussels Airport.

Find out what your peers are saying about Apache, Cloudera, Amazon Web Services (AWS) and others in Hadoop. Updated: February 2025.

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