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Elastic Search vs Weka 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:
 

Categories and Ranking

Elastic Search
Average Rating
8.2
Reviews Sentiment
6.8
Number of Reviews
71
Ranking in other categories
Indexing and Search (1st), Cloud Data Integration (9th), Search as a Service (1st), Vector Databases (3rd)
Weka
Average Rating
7.6
Reviews Sentiment
6.8
Number of Reviews
14
Ranking in other categories
Data Mining (2nd), Anomaly Detection Tools (4th)
 

Mindshare comparison

Elastic Search and Weka aren’t in the same category and serve different purposes. Elastic Search is designed for Indexing and Search and holds a mindshare of 23.1%, down 27.8% compared to last year.
Weka, on the other hand, focuses on Data Mining, holds 17.7% mindshare, down 21.1% since last year.
Indexing and Search
Data Mining
 

Featured Reviews

Anand_Kumar - PeerSpot reviewer
Captures data from all other sources and becomes a MOM aka monitoring of monitors
Scalability and ROI are the areas they have to improve. Their license terms are based on the number of cores. If you increase the number of cores, it becomes very difficult to manage at a large scale. For example, if I have a $3 million project, I won't sell it because if we're dealing with a 10 TB or 50 TB system, there are a lot of systems and applications to monitor, and I have to make an MOM (Mean of Max) for everything. This is because of the cost impact. Also, when you have horizontal scaling, it's like a multi-story building with only one elevator. You have to run around, and it's not efficient. Even the smallest task becomes difficult. That's the problem with horizontal scaling. They need to improve this because if they increase the cores and adjust the licensing accordingly, it would make more sense.
AwaisAnwar - PeerSpot reviewer
Open source, good for basic data mining use cases except for the visualization results
I haven't found it particularly useful. It lacks state-of-the-art algorithms and impressive outcomes. While it might offer insights for basic warehouse tasks, it falls short of deeper understanding and results. Moreover, a new user interface would be great, especially for beginners. Something that guides them through the available tools and helps them achieve their goals. I haven't seen anything like that myself, though maybe it's there and I missed it.

Quotes from Members

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

Pros

"I like how it allows us to connect to Kafka and get this data in a document format very easily. Elasticsearch is very fast when you do text-based searches of documents. That area is very good, and the search is very good."
"The most valuable feature of the solution is its utility and usefulness."
"The UI is very nice, and performance wise it's quite good too."
"The special text processing features in this solution are very important for me."
"I appreciate the indexing capabilities and the speed of indexing in their product, which demonstrates how quickly logs are collected and stored."
"The most valuable features are the ease and speed of the setup."
"I have found the sort capability of Elastic very useful for allowing us to find the information we need very quickly."
"I find the solution to be fast."
"I like the machine algorithm for clustering systems. Weka has larger capabilities. There are multiple algorithms that can be used for clustering. It depends upon the user requirements. For clustering, I've used DBSCAN, whereas for supervised learning, I've used AVM and RFT."
"Weka's best features are its user-friendly graphic interface interpretation of data sets and the ease of analyzing data."
"Weka eliminates the need for coding, allowing you to easily set parameters and complete the majority of the machine learning task with just a few clicks."
"The interface is very good, and the algorithms are the very best."
"It is a stable product."
"With clustering, if it's a yes, it's a yes, if it's a no, it's a no. It gives you a 100% level of accuracy of a model that has been trained, and that is in most cases, usually misleading. Classification is highly valuable when done as opposed to clustering."
"There are many options where you can fill all of the data pre-processing options that you can implement when you're importing the data. You can also normalize the data and standardize it in an easier way."
"I mainly use this solution for the regression tree, and for its association rules. I run these two methodologies for Weka."
 

Cons

"I would like to see more integration for the solution with different platforms."
"There should be more stability."
"They could improve some of the platform's infrastructure management capabilities."
"The one area that can use improvement is the automapping of fields."
"I would like to be able to do correlations between multiple indexes."
"Elasticsearch could improve by honoring Unix environmental variables and not relying only on those provided by Java (e.g. installing plugins over the Unix http proxy)."
"There is another solution I'm testing which has a 500 record limit when you do a search on Elastic Enterprise Search. That's the only area in which I'm not sure whether it's a limitation on our end in terms of knowledge or a technical limitation from Elastic Enterprise Search. There is another solution we are looking at that rides on Elastic Enterprise Search. And the limit is for any sort of records that you're doing or data analysis you're trying to do, you can only extract 500 records at a time. I know the open-source nature has a lot of limitations, Otherwise, Elastic Enterprise Search is a fantastic solution and I'd recommend it to anyone."
"Enterprise scaling of what have been essentially separate, free open source software (FOSS) products has been a challenge, but the folks at Elastic have published new add-ons (X-Pack and ECE) to help large companies grow ELK to required scales."
"The visualization of Weka is subpar and could improve. Machine learning and visualization do not work well together. For example, we want to know how we can we delete empty cells or how can we fill in the empty cells without cleaning the data system and putting it together."
"If there are a lot more lines of code, then we should use another language."
"Weka could be more stable."
"I believe is there are a few newer algorithms that are not present in the Weka libraries. Whereas, for example, if I want to have a solution that involves deep learning, so I don't think that Weka has that capability. So in that case I have to use Python for ... predict any algorithms based on deep learning."
"The filter section lacks some specific transformation tools. If you want to change a variable from a numeric variable to a categorical variable, you don't have a feature that can enable you to change a variable from a numeric variable to a categorical variable."
"In terms of scalability, I think Weka is not prepared to handle a large number of users."
"The product is good, but I would like it to work with big data. I know it has a Spark integration they could use to do analysis in clusters, but it's not so clear how to use it."
"Weka is a little complicated and not necessarily suited for users who aren't skilled and experienced in data science."
 

Pricing and Cost Advice

"The version of Elastic Enterprise Search I am using is open source which is free. The pricing model should improve for the enterprise version because it is very expensive."
"Elastic Search is open-source, but you need to pay for support, which is expensive."
"The basic license is free, but it comes with a lot of features that aren't free. With a gold license, we get active directory integration. With a platinum license, we get alerting."
"The pricing model is questionable and needs to be addressed because when you would like to have the security they charge per machine."
"we are using a licensed version of the product."
"We use the free version for some logs, but not extensive use."
"​The pricing and license model are clear: node-based model."
"Although the ELK Elasticsearch software is open-source, we buy the hardware."
"Currently, I am using an open-source version so I don't know much about the price of this solution."
"We use the free version now. My faculty is very small."
"As far as I know, Weka is a freeware tool, and I am not aware if they have an online solution or if it is a commercial product."
"The solution is free and open-source."
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Top Industries

By visitors reading reviews
Computer Software Company
16%
Financial Services Firm
14%
Government
9%
Manufacturing Company
9%
University
17%
Educational Organization
16%
Computer Software Company
11%
Financial Services Firm
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

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?
It would be useful if a feature for renaming indices could be added without affecting the performance of other features. However, overall, the consistency and stability of Elasticsearch are already...
What is your experience regarding pricing and costs for Weka?
Weka is free and open-source software. That is why I used it over KNIME.
What needs improvement with Weka?
I haven't found it particularly useful. It lacks state-of-the-art algorithms and impressive outcomes. While it might offer insights for basic warehouse tasks, it falls short of deeper understanding...
 

Comparisons

 

Also Known As

Elastic Enterprise Search, Swiftype, Elastic Cloud
No data available
 

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.
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Find out what your peers are saying about Elastic Search vs. Weka and other solutions. Updated: January 2022.
859,957 professionals have used our research since 2012.