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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
3.8
Organizations using Elastic Search reported improved efficiency, faster performance, cost savings, and enhanced data management, emphasizing positive outcomes.
Sentiment score
7.4
Pentaho and Lumada integration improved efficiency, reduced costs, and enhanced decision-making speed, benefiting companies' competitiveness and project wins.
We have not purchased any licensed products, and our use of Elastic Search is purely open-source, contributing positively to our ROI.
Software Engineer at Government of India
It is stable, and we do not encounter critical issues like server downtime, which could result in data loss.
SOC A2 at Innodata-ISOGEN
The main benefits observed from using Elastic Search include improvements in operational efficiency, along with cost, time, and resource savings.
Senior Devops Engineer at Ubique Digital LTD
I have seen a return on investment; my team was able to stay extremely small even though we had a lot of data integrations with many companies.
Principal Software Engineer at a tech vendor with 10,001+ employees
I can testify to the return on investment with metrics regarding time saved; we have increased our efficiency by about 20 to 30 percent due to the swift migration processes facilitated by the tool.
Data Integration Developer at a tech services company with 1,001-5,000 employees
I have noticed a return on investment with Pentaho Data Integration and Analytics in terms of time savings and staff reduction.
Data Analyst at Telefonica Digital
 

Customer Service

Sentiment score
6.3
Elastic Search customer service is praised for responsiveness and expertise, though some users note occasional slow responses.
Sentiment score
5.1
Pentaho support experiences vary; some note effectiveness, others delays, with community forums often supplementing Enterprise's speedy ticket responses.
For P1 tickets, they provide very immediate quick responses and join calls to support and troubleshoot the issue accordingly.
Elastic Engineer at The Unique Identification Authority of India (UIDAI)
The customer support for Elastic Search is one of the best I have ever tried.
Software Developer at a media company with 10,001+ employees
They have always been really responsible and responsive to my requests.
Security Lead at a tech vendor with 501-1,000 employees
24/7 assistance is available for the Enterprise Edition.
Data architect at a tech vendor with 10,001+ employees
take the time to understand our business requirements, offering appropriate recommendations.
Data Integration Developer at a tech services company with 1,001-5,000 employees
Communication with the vendor is challenging
Data Architecture and Engineering Specialist at coprocenva
 

Scalability Issues

Sentiment score
7.2
Elastic Search is scalable and reliable for high-volume tasks, though some users face challenges with cost and complex data handling.
Sentiment score
7.2
Pentaho Data Integration offers good scalability for moderate datasets but struggles with large volumes and cloud architectures.
We can search through that document quite easily, sometimes in 7 milliseconds, sometimes one or two milliseconds.
Product Engineer at A3L
Performance tests involving one million requests at once, we encountered issues with shards and nodes not upscaling as needed, leading to crashes and minimal data loss.
Consultant at a tech vendor with 10,001+ employees
I would rate its scalability a ten.
Backend Developer
It can be scaled well until you reach a point where you need to perform a lot of operations, and the issue arises when it runs out of memory to handle some data.
Data engineer at a educational organization with 1,001-5,000 employees
Its ability to scale horizontally in cloud-native architectures or for massive real-time processing is limited.
Data Analyst at Telefonica Digital
Pentaho Data Integration handles larger datasets better.
Data Architecture and Engineering Specialist at coprocenva
 

Stability Issues

Sentiment score
7.7
Elastic Search is reliable, especially under one terabyte, with occasional issues and challenges from frequent updates.
Sentiment score
7.2
Pentaho is stable and reliable, though minor bugs and performance issues occur, especially with older or complex queries.
The data transfer sometimes exceeded the bandwidth limits without proper notification, which caused issues.
SOC A2 at Innodata-ISOGEN
The stability of Elasticsearch was very high.
Backend Developer
When you put one keyword, everything related to that keyword in your ecosystem will showcase all the results.
Chief Information Security Officer at CDSL Ventures Limited
Performance issues arise due to reliance on a flowchart-based mechanism instead of scripts, which can lead to longer execution times.
Data architect at a tech vendor with 10,001+ employees
I find that version 3.1 is the most stable version I have ever used.
Founder-CEO at Ubuntu Analytica
It's pretty stable, however, it struggles when dealing with smaller amounts of data.
Data Architecture and Engineering Specialist at coprocenva
 

Room For Improvement

Users criticize Elastic Search for mapping conflicts, complex setup, high costs, and desire improved AI integration and better documentation.
Pentaho requires better cloud adaptability, scalability, real-time processing, modern UI, language support, performance, documentation, and environment compatibility.
From a technical point of view, there are no significant issues recalled as Elastic Search has been absolutely awesome for this use case and covers 100% of the needs.
Principal Scientific Computing Software Engineer at a educational organization with 1,001-5,000 employees
If I need to parse one million records saved into Elastic Search, it becomes a nightmare because I need to do the pagination, and it is very problematic in that regard.
Lead Engineer at Spidersilk
Observability features like search latency, indexing rate, and maybe rejected requests should be added to make the platform more reliable and accessible for everyone.
Senior System Engineer at EPAM Systems
We should also explore more effective partitioning for parallel processing and fine-tuning database connections to reduce load times and improve ETL speed.
Data Integration Developer at a tech services company with 1,001-5,000 employees
Pentaho Data Integration and Analytics can be improved by working with different environments, specifically the possibility to change the variables, meaning I write my variables only once and can change them for different environments such as production or development.
Founder-CEO at Ubuntu Analytica
Pentaho Data Integration and Analytics could have real-time processing and automatic alerting, having alerts or automatic notifications when a job fails or when certain data doesn't meet certain rules.
Data Analyst at Telefonica Digital
 

Setup Cost

Elastic Search offers enterprise pricing based on nodes, with costs varying by features, support, and deployment options.
Pentaho offers a cost-effective solution with appealing Community and Enterprise editions, maintaining positive sentiment despite some price increases.
On the AWS side, it is very expensive because they charge based on query basis or how much data is transferred in and out, making it very expensive.
Lead Engineer at Spidersilk
Having the hosted solution and not having to pay for essentially a DevOps person on staff to manage makes it affordable.
CTO at a tech services company with 1-10 employees
You can host it on-premises, which would incur zero cost, or take it as a SaaS-based service, where the expenses remain minimal.
Senior Software Engineer at Agoda
I use the community version of Pentaho Data Integration and Analytics, and I do not need additional costs.
Project Manager at Laberit
The setup cost was minimal, and the pricing experience was pretty good.
Data engineer at a educational organization with 1,001-5,000 employees
The company covered it and they had no problem paying for it because they saw that it was cost-effective in terms of performance afterwards.
Data Analyst at Telefonica Digital
 

Valuable Features

Elastic Search enhances data handling with advanced search features, scalability, AI integrations, and powerful visualization via Kibana.
Pentaho offers intuitive data integration with broad connectivity, simplifying complex transformations and providing flexibility and automation across environments.
Elastic Search makes handling large data volumes efficient and supports complex search operations.
Software Engineer at Government of India
The most valuable feature of Elasticsearch was the quick search capability, allowing us to search by any criteria needed.
Backend Developer
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.
Director, Software Engineering at a tech vendor with 10,001+ employees
Pentaho Data Integration and Analytics has positively impacted my organization because it meant we didn't have to write a lot of custom API back-end processing logic; it did the majority of that heavy lifting for us.
Principal Software Engineer at a tech vendor with 10,001+ employees
It automates the data workflow, including extraction, cleansing, and loading into warehouses for BI reporting purposes, while also removing duplicates, validating data, and standardizing formats, enabling real-time decision-making.
Data Integration Developer at a tech services company with 1,001-5,000 employees
Pentaho Data Integration and Analytics has positively impacted my organization because it is easier to use, and my knowledge about this work facilitates the translation from the source to my final system.
Project Manager at Laberit
 

Categories and Ranking

Elastic Search
Average Rating
8.2
Reviews Sentiment
6.5
Number of Reviews
96
Ranking in other categories
Indexing and Search (1st), Cloud Data Integration (5th), Search as a Service (1st), Vector Databases (2nd)
Pentaho Data Integration an...
Average Rating
8.0
Reviews Sentiment
6.7
Number of Reviews
60
Ranking in other categories
Data Integration (7th)
 

Featured Reviews

reviewer2817942 - PeerSpot reviewer
Senior Software Engineer at a consultancy with 11-50 employees
Logging and vector search have transformed observability and empowered reliable ai agents
Elastic Search is not specifically being used for certain purposes. I deploy Elastic Search database on the cloud and use cloud services so that nobody can attack. However, I do not use Elastic Search to resolve attack issues. The basic main purpose of Elastic Search, as of now, I feel it can do more in the AI area. Sometime I saw that when I am developing RAG and have to generate the embeddings, which I call metadata, sometimes it tries to fail. That durability or issue handling should be improved, but apart from that, I did not find anything as of now. As per my use case, whatever I am using seems pretty good. Apart from that, some definitely improvement will be there. One improvement is that it should be faster. Whenever I am searching any logs, it takes much time. For example, if I open my log in Notepad or a similar tool, I can search the text within a second. With Elastic Search, it takes a little bit of time, ten to fifteen seconds. That can be improved. Sometimes, engineers take time to assign when I create a ticket.
Michelle Lawson - PeerSpot reviewer
Principal Software Engineer at a tech vendor with 10,001+ employees
Streamlines complex data workflows and has supported automated customer payment notifications
I haven't used Pentaho Data Integration and Analytics in a couple of years, so I don't know how it can be improved. I was pretty pleased with it and was self-taught on it, working a lot with their team at various times, but they were surprised that I was able to learn it all by myself. The documentation is not bad, and documentation is the main thing that any product can do to make themselves better because the easier it is to find examples of what you're trying to do improves the learning curve. I think it took me the longest to learn how to do the asynchronous processing and have things wait for other things to finish processing before continuing on in the workflow. I choose 8 out of 10 because the one reason that it's been rejected at T-Mobile is that everything has to go through a provisioning process and has to get approved, meaning the actual code base has to be investigated by T-Mobile before they'll allow us to use tools of that nature. For whatever reason, we just haven't been able to get that approval; I don't know if it's on Pentaho Data Integration and Analytics' side or if it's on our side. The more you can make it easier for companies to feel comfortable that your product is secure, robustly tested and bug-free, and free of any other kind of negative hacks, the more quickly it will get accepted.
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Top Industries

By visitors reading reviews
Financial Services Firm
12%
Computer Software Company
9%
Manufacturing Company
9%
Retailer
6%
Financial Services Firm
15%
Educational Organization
8%
Government
7%
Manufacturing Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business39
Midsize Enterprise12
Large Enterprise47
By reviewers
Company SizeCount
Small Business18
Midsize Enterprise17
Large Enterprise31
 

Questions from the Community

What is your experience regarding pricing and costs for ELK Elasticsearch?
When it comes to pricing, I think we had to pay AWS approximately 1,000 to 1,200 per month for the overall stack. I am not quite certain about how much Elastic Search costs specifically because I w...
What needs improvement with ELK Elasticsearch?
Elastic Search has many features, including Kibana and Logstash, which we regularly use. However, one downside in our product is cost, as it can be expensive when maintaining multiple shards and in...
What is your primary use case for ELK Elasticsearch?
As a developer, I use Elastic Search in developing one of my applications, basically integrating the back-end with Elastic Search. Our main use case for Elastic Search is for Logstash, which is a s...
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: April 2026.
894,738 professionals have used our research since 2012.