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Elastic Search vs Pentaho Data Integration and Analytics comparison

 

Comparison Buyer's Guide

Executive Summary

Review summaries and opinions

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

ROI

Sentiment score
5.2
Elastic Search offers efficiency and cost-saving benefits, though some face limited returns due to licensing and implementation issues.
Sentiment score
7.9
Pentaho offers cost-effective integration, reducing ETL time, lowering expenses, and enhancing competitiveness with open-source flexibility and efficiency.
We have not purchased any licensed products, and our use of Elastic Search is purely open-source, contributing positively to our ROI.
It is stable, and we do not encounter critical issues like server downtime, which could result in data loss.
The main benefits observed from using Elastic Search include improvements in operational efficiency, along with cost, time, and resource savings.
 

Customer Service

Sentiment score
6.3
Elastic Search's support is praised for responsiveness but criticized for delays, with users often relying on community resources.
Sentiment score
5.2
Users rely on community support over customer service due to mixed experiences, despite responsive technical support and Hitachi's involvement.
The customer support for Elastic Search is one of the best I have ever tried.
They have always been really responsible and responsive to my requests.
I would rate technical support from Elastic Search as three out of ten.
Communication with the vendor is challenging
 

Scalability Issues

Sentiment score
7.2
Elastic Search offers scalable expansion, accommodating data growth and diverse needs, though it presents challenges with disaster recovery.
Sentiment score
7.3
Pentaho excels in scalability and efficient data handling but faces challenges with exceptionally large data and complex growth scenarios.
I would rate its scalability a ten.
Since we're on the cloud, whenever we need to upgrade or add resources, they handle everything.
I can actually add more storage and memory because I host it in the cloud.
Pentaho Data Integration handles larger datasets better.
 

Stability Issues

Sentiment score
7.7
Elastic Search is highly regarded for stability, despite occasional memory challenges, with users rating it between seven and ten.
Sentiment score
7.1
Pentaho Data Integration offers reliability for small to midsize operations but may lag and freeze with complex uses.
The data transfer sometimes exceeded the bandwidth limits without proper notification, which caused issues.
The stability of Elasticsearch was very high.
Elastic Search is quite stable.
It's pretty stable, however, it struggles when dealing with smaller amounts of data.
 

Room For Improvement

Elasticsearch needs improvements in security, scalability, tool integration, user experience, support, and cost clarity to enhance usability.
Pentaho needs improvements in big data performance, error handling, UI, scheduling, backward compatibility, cloud integration, and Python support.
This can create problems for new developers because they have to quickly switch to another version.
It is primarily based on Unix or Linux-based operating systems and cannot be easily configured in Windows systems.
The consistency and stability of Elasticsearch are commendable, and they should keep up the good work.
Pentaho Data Integration is very friendly, it is not very useful when there isn't a lot of data to handle.
 

Setup Cost

Elastic Search is open-source, but enterprise features and managed services can significantly increase costs and create pricing complexity.
Pentaho offers a cost-effective solution with its free Community Edition and affordable subscription-based Enterprise Edition for varying needs.
We used the open-source version of Elasticsearch, which was free.
Elastic pushes clients to buy the Enterprise edition instead of the Premium edition, and we don't see the value in that other than to spend more money more quickly.
 

Valuable Features

Elastic Search offers fast, scalable log monitoring, data indexing, visualization, robust queries, and machine learning, enhancing usability and stability.
Pentaho provides an intuitive, open-source platform for efficient ETL development and data integration with minimal coding and broad compatibility.
Elastic Search makes handling large data volumes efficient and supports complex search operations.
The most valuable feature of Elasticsearch was the quick search capability, allowing us to search by any criteria needed.
The speed with which Elastic Search is able to search through all of the documents we place into it is quite remarkable, as we search through 65 billion documents in less than a second in most cases, on a constant consistent basis.
I find the drag and drop feature in Pentaho Data Integration very useful for integration.
 

Categories and Ranking

Elastic Search
Average Rating
8.2
Reviews Sentiment
6.6
Number of Reviews
75
Ranking in other categories
Indexing and Search (1st), Cloud Data Integration (9th), Search as a Service (1st), Vector Databases (3rd)
Pentaho Data Integration an...
Average Rating
8.0
Reviews Sentiment
6.9
Number of Reviews
53
Ranking in other categories
Data Integration (18th)
 

Featured Reviews

Louis McCoy - PeerSpot reviewer
Searches through billions of documents have become impressively fast and consistent
The seamless scalability is something I see as among the best features Elastic Search offers. The speed with which Elastic Search is able to search through all of the documents we place into it is quite remarkable, as we search through 65 billion documents in less than a second in most cases, on a constant consistent basis. I find configuring relevant searches within Elastic Search platform very straightforward. Elastic Search is easily scalable. The customer support for Elastic Search is quite good. I advise others looking into using Elastic Search to think about the future of your platform and where you intend it to be in five years, and based on that, which version of Elastic Search best suits the needs of your platform. Additionally, jump into the AI products first as you're in the planning phase so that as you're filling out your data, the AI products and machine learning products can enrich the data real-time early on in the process, which will save you a lot of time later. The overall performance of the platform, scalability of the platform and other additional features, especially when it comes to AI, really earn the nine.
Aqeel UR Rehman - PeerSpot reviewer
Transform data efficiently with rich features but there's challenges with large datasets
Currently, I am using Pentaho Data Integration for transforming data and then loading it into different platforms. Sometimes, I use it in conjunction with AWS, particularly S3 and Redshift, to execute the copy command for data processing Pentaho Data Integration is easy to use, especially when…
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Top Industries

By visitors reading reviews
Computer Software Company
14%
Financial Services Firm
13%
Manufacturing Company
8%
Government
8%
Financial Services Firm
18%
Computer Software Company
11%
Government
8%
Manufacturing Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business32
Midsize Enterprise9
Large Enterprise36
By reviewers
Company SizeCount
Small Business17
Midsize Enterprise16
Large Enterprise25
 

Questions from the Community

What do you like most about ELK Elasticsearch?
Logsign provides us with the capability to execute multiple queries according to our requirements. The indexing is very high, making it effective for storing and retrieving logs. The real-time anal...
What is your experience regarding pricing and costs for ELK Elasticsearch?
We used the open-source version of Elasticsearch, which was free.
What needs improvement with ELK Elasticsearch?
We could benefit from refining the machine learning models that we currently use in Elastic Search, along with the possibility to integrate agents, intelligent artificial intelligence, form of agen...
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...
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, ...
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...
 

Also Known As

Elastic Enterprise Search, Swiftype, Elastic Cloud
Hitachi Lumada Data Integration, Kettle, Pentaho Data Integration
 

Overview

 

Sample Customers

T-Mobile, Adobe, Booking.com, BMW, Telegraph Media Group, Cisco, Karbon, Deezer, NORBr, Labelbox, Fingerprint, Relativity, NHS Hospital, Met Office, Proximus, Go1, Mentat, Bluestone Analytics, Humanz, Hutch, Auchan, Sitecore, Linklaters, Socren, Infotrack, Pfizer, Engadget, Airbus, Grab, Vimeo, Ticketmaster, Asana, Twilio, Blizzard, Comcast, RWE and many others.
66Controls, Providential Revenue Agency of Ro Negro, NOAA Information Systems, Swiss Real Estate Institute
Find out what your peers are saying about Elastic Search vs. Pentaho Data Integration and Analytics and other solutions. Updated: September 2025.
869,760 professionals have used our research since 2012.