Compare ELK Elasticsearch vs. Weka

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ELK Elasticsearch Logo
4,039 views|2,603 comparisons
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Read 7 Weka reviews.
2,919 views|2,685 comparisons
Most Helpful Review
Find out what your peers are saying about ELK Elasticsearch vs. Weka and other solutions. Updated: January 2021.
456,966 professionals have used our research since 2012.
Quotes From Members

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

Pros
"We had many reasons to implement Elasticsearch for search term solutions. Elasticsearch products provide enterprise landscape support for different areas of the company.""The most valuable feature for us is the analytics that we can configure and view using Kibana.""The special text processing features in this solution are very important for me.""The most valuable features are the data store and the X-pack extension.""I value the feature that allows me to share the dashboards to different people with different levels of access.""The product is scalable with good performance.""Dashboard is very customizable.""There's lots of processing power. You can actually just add machines to get more performance if you need to. It's pretty flexible and very easy to add another log. It's not like 'oh, no, it's going to be so much extra data'. That's not a problem for the machine. It can handle it."

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"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.""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.""Weka is a very nice tool, it needs very small requirements. If I want to implement something in Python, I need a lot of memory and space but Weka is very lightweight. Anyone can implement any kind of algorithm, and we can show the results immediately to the client using the one-page feature. The client always wants to know the story. They want the result.""Working with complicated algorithms in huge datasets is really easy in Weka.""The path of machine learning in classification and clustering is useful. The GUI can get you results. No programming is needed. No need to write down your script first or send to your model or input your data.""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."

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Cons
"We see the need for some improvements with Elasticsearch. We would like the Elasticsearch package to include training lessons for our staff.""This product could be improved with additional security, and the addition of support for machine learning devices.""Better dashboards or a better configuration system would be very good.""The pricing of this product needs to be more clear because I cannot understand it when I review the website.""Ratio aggregation is not supported in this solution.""The GUI is the part of the program which has the most room for improvement.""Could have more open source tools and testing.""The solution has quite a steep learning curve. The usability and general user-friendliness could be improved. However, that is kind of typical with products that have a lot of flexibility, or a lot of capabilities. Sometimes having more choices makes things more complex. It makes it difficult to configure it, though. It's kind of a bitter pill that you have to swallow in the beginning and you really have to get through it."

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"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.""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.""Within the basic Weka tool, I don't see many tools that are available where we can analyze and visualize the data that well.""If there are a lot more lines of code, then we should use another language.""Not particularly user friendly.""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."

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Pricing and Cost Advice
"We are using the free version and intend to upgrade.""It can be expensive.""This product is open-source and can be used free of charge.""We are using the open-sourced version.""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."

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

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Questions from the Community
Top Answer: Dashboard is very customizable.
Top Answer: I would like to see more open source tools and testing as well as a signature analysis in the solution. I think that a lot of times when we go into a corporate environment where it becomes more add on… more »
Top Answer: In terms of use case, we combine a lot of things with Elastic. It's two platforms, so with Elasticsearch, we're using the Beats, Kibana, and Suricata. It's a query engine and we use the information… more »
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4,039
Comparisons
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Reviews
14
Average Words per Review
601
Rating
8.1
Views
2,919
Comparisons
2,685
Reviews
7
Average Words per Review
1,001
Rating
7.3
Popular Comparisons
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Overview
Elasticsearch is a distributed, JSON-based search and analytics engine designed for horizontal scalability, maximum reliability, and easy management. Elasticsearch lets you perform and combine many types of searches — structured, unstructured, geo, metric — any way you want.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.
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Sample Customers
HotelTonight, Perceivant, Docker, Green Man Gaming, Xoom, AutoScout24, TheLadders, Center for Open Science, Parleys, Tango
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Top Industries
REVIEWERS
Financial Services Firm43%
Transportation Company14%
University14%
Government14%
VISITORS READING REVIEWS
Computer Software Company23%
Comms Service Provider18%
Media Company15%
Manufacturing Company5%
VISITORS READING REVIEWS
Comms Service Provider27%
Educational Organization18%
Computer Software Company16%
Financial Services Firm7%
Company Size
REVIEWERS
Small Business50%
Midsize Enterprise14%
Large Enterprise36%
No Data Available
Find out what your peers are saying about ELK Elasticsearch vs. Weka and other solutions. Updated: January 2021.
456,966 professionals have used our research since 2012.

ELK Elasticsearch is ranked 2nd in Anomaly Detection Tools with 15 reviews while Weka is ranked 3rd in Anomaly Detection Tools with 7 reviews. ELK Elasticsearch is rated 8.0, while Weka is rated 7.2. The top reviewer of ELK Elasticsearch writes "Good processing power, very scalable, and able to handle all data formats". On the other hand, the top reviewer of Weka writes "Relatively stable with excellent accuracy and there's no need to know coding". ELK Elasticsearch is most compared with Amazon Athena, Azure Search, Amazon AWS CloudSearch, Splunk User Behavior Analytics and Qbox, whereas Weka is most compared with KNIME, IBM SPSS Statistics, IBM SPSS Modeler, SAS Analytics and FICO Model Builder. See our ELK Elasticsearch vs. Weka report.

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