Elastic Search vs Weka comparison

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Elastic Search

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Executive Summary

We performed a comparison between Elastic Search and Weka based on real PeerSpot user reviews.

Find out in this report how the two Indexing and Search solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed Elastic Search vs. Weka Report (Updated: January 2022).

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Elastic Search vs. Weka

January 2022

Helped 831,265 peers since 2012

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

Ranking in other categories

Indexing and Search (1st), Cloud Data Integration (11th), Search as a Service (1st), Vector Databases (1st)

Weka

Average Rating

7.6

Number of Reviews

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 28.4%, up 25.2% compared to last year.
Weka, on the other hand, focuses on Data Mining, holds 21.6% mindshare, up 19.5% since last year.

Indexing and Search

Data Mining

Featured Reviews

Anand_Kumar

Enterprise Architect at DXC Technology

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.

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AwaisAnwar

Treasury Management in Finance Department at National University of Pakistan

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.

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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

"The initial setup is very easy for small environments."

"The solution is valuable for log analytics."

"It provides deep visibility into your cloud and distributed applications, from microservices to serverless architectures. It quickly identifies and resolves the root causes of issues, like gaining visibility into all the cloud-based and on-prem applications."

"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 analytics with Elastic benefits us due to the huge traffic volume in our organization, which reaches up to 60,000 requests per second. With logs of approximately 25 GB per day, manually analyzing traffic behavior, payloads, headers, user agents, and other details is impractical."

"The solution has good security features. I have been happy with the dashboards and interface."

"The products comes with REST APIs."

"Using real-time search functionality to support operational decisions has been helpful."

"The observability is the best available because it provides granular insights that identify reasons for defects."

More Elastic Search pros

"Working with complicated algorithms in huge datasets is really easy in Weka."

"It doesn’t cost anything to use the product."

"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."

"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."

"The interface is very good, and the algorithms are the very best."

"It is a stable product."

"I mainly use this solution for the regression tree, and for its association rules. I run these two methodologies for Weka."

"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."

More Weka pros

Cons

"Elastic Enterprise Search can improve by adding some kind of search that can be used out of the box without too much struggle with configuration. With every kind of search engine, there is some kind of special function that you need to do. A simple out-of-the-box search would be useful."

"There are challenges with performance management and scalability."

"Elastic Search should provide better guides for developers."

"It should be easier to use. It has been getting better because many functions are pre-defined, but it still needs improvement."

"There is a lack of technical people to develop, implement and optimize equipment operation and web queries."

"While integrating with tools like agents for ingesting data from sources like firewalls is valuable, I believe prioritizing improvements to the core product would be more beneficial."

"New Relic could be more flexible, similar to Elasticsearch."

"Elastic Search could benefit from a more user-friendly onboarding process for beginners."

More Elastic Search cons

"A few people said it became slow after a while."

"In terms of scalability, I think Weka is not prepared to handle a large number of users."

"While it might offer insights for basic warehouse tasks, it falls short of deeper understanding and results."

"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."

"Within the basic Weka tool, I don't see many tools that are available where we can analyze and visualize the data that well."

"Not particularly user friendly."

"Weka is a little complicated and not necessarily suited for users who aren't skilled and experienced in data science."

"If you have one missing value in your dataset and this missing value belongs to a specific attribute and the attribute is a numeric attribute and there is only one missing data, whenever you import this data, the problem is that Weka cannot understand that this is a numeric field. It converts everything into a string, and there is no way to convert the string into numerical math. It's really very complicated."

More Weka cons

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."

"The price of Elasticsearch is fair. It is a more expensive solution, like QRadar. The price for Elasticsearch is not much more than other solutions we have."

"To access all the features available you require both the open source license and the production license."

"It can be expensive."

"We are using the Community Edition because Elasticsearch's licensing model is not flexible or suitable for us. They ask for an annual subscription. We also got the development consultancy from Elasticsearch for 60 days or something like that, but they were just trying to do the same trick. That's why we didn't purchase it. We are just using the Community Edition."

"The premium license is expensive."

"The solution is less expensive than Stackdriver and Grafana."

"This is a free, open source software (FOSS) tool, which means no cost on the front-end. There are no free lunches in this world though. Technical skill to implement and support are costly on the back-end with ELK, whether you train/hire internally or go for premium services from Elastic."

More Elastic Search pricing and cost advice

"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."

"We use the free version now. My faculty is very small."

"Currently, I am using an open-source version so I don't know much about the price of this solution."

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Top Industries

By visitors reading reviews

Computer Software Company

18%

Financial Services Firm

15%

Manufacturing Company

Government

University

20%

Educational Organization

14%

Computer Software Company

10%

Financial Services Firm

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?

I am not directly involved with pricing or setup costs. While I know a portion is open-source, a paid version might be necessary.

What needs improvement with ELK Elasticsearch?

There should be more stability. When we started learning it, new versions came out frequently in one quarter with extended features. This can create problems for new developers because they have to...

What do you like most about Weka?

It is a stable product.

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?

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Compared 16% of the time

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Compared 7% of the time

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Product Reports

Download Elastic Search product report

Elastic Search

January 2025

Download Weka product report

December 2024

Also Known As

Elastic Enterprise Search, Swiftype, Elastic Cloud

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Elastic

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Overview

Elasticsearch is a prominent open-source search and analytics engine known for its scalability, reliability, and straightforward management. It's a favored choice among enterprises for real-time data search, analysis, and visualization. Open-source Elasticsearch is free, offering a comprehensive feature set and scalability. It allows full control over deployments but requires managing and maintaining the infrastructure. On the other hand, Elastic Cloud provides a managed service with features like automated provisioning, high availability, security, and global reach.

Elasticsearch excels in handling time-sensitive data and complex search requirements across large datasets. Its scalability allows it to handle growing data volumes efficiently, maintaining high performance and fast response times. Integrated with Kibana, Elasticsearch enables powerful data visualization, providing real-time insights crucial for data-driven decision-making.

Elastic Cloud reduces operational overhead and improves scalability and performance, though it comes with associated costs. It is available on your preferred cloud provider — AWS, Azure, or Google Cloud. Customers who want to manage the software themselves, whether on public, private, or hybrid cloud, can download the Elastic Stack.

At its core, Elasticsearch is renowned for its full-text search capabilities, capable of performing complex queries and supporting features like fuzzy matching and auto-complete.

Peer reviews from various professionals highlight its strengths and weaknesses. Pros include its detection and correlation features, flexibility, cloud-readiness, extensibility, and efficient search capabilities. However, users have noted challenges like steep learning curves, data analysis limitations, and integration complexities. The platform is generally viewed as stable and scalable, with varying degrees of satisfaction regarding its usability and feature set.

In summary, Elasticsearch stands out for its high-speed search, scalability, and versatile analytics, making it a go-to solution for organizations managing large datasets. Its adaptability to different enterprise needs, robust community support, and continuous development keep it at the forefront of enterprise search and analytics solutions. However, potential users should be aware of its learning curve and the need for skilled personnel for optimization.

Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes.

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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