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."I appreciate that Elastic Enterprise Search is easy to use and that we have people on our team who are able to manage it effectively."
"I have found the sort capability of Elastic very useful for allowing us to find the information we need very quickly."
"The most valuable feature is the out of the box Kibana."
"ELK Elasticsearch is 100% scalable as scalability is built into the design"
"It is easy to scale with the cluster node model."
"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."
"Gives us a more user-friendly, centralized solution (for those who just needed a quick glance, without being masters of sed and awk) as well as the ability to implement various mechanisms for machine-learning from our logs, and sending alerts for anomalies."
"The products comes with REST APIs."
"It doesn’t cost anything to use the product."
"The interface is very good, and the algorithms are the very best."
"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."
"It is a stable product."
"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."
"Weka's best features are its user-friendly graphic interface interpretation of data sets and the ease of analyzing data."
"Working with complicated algorithms in huge datasets is really easy in Weka."
"The solution's integration and configuration are not easy. Not many people know exactly what to do."
"This product could be improved with additional security, and the addition of support for machine learning devices."
"We have an issue with the volume of data that we can handle."
"Technical support should be faster."
"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 one area that can use improvement is the automapping of fields."
"Both the graph feature and the reporting feature are a little bit lacking. The alerting also needs to be improved."
"They're making changes in their architecture too frequently."
"While it might offer insights for basic warehouse tasks, it falls short of deeper understanding and results."
"Not particularly user friendly."
"If there are a lot more lines of code, then we should use another language."
"Weka could be more stable."
"Within the basic Weka tool, I don't see many tools that are available where we can analyze and visualize the data that well."
"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."
"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."
"In terms of scalability, I think Weka is not prepared to handle a large number of users."
Elastic Search is ranked 1st in Indexing and Search with 59 reviews while Weka is ranked 2nd in Data Mining with 14 reviews. Elastic Search is rated 8.2, while Weka is rated 7.6. The top reviewer of Elastic Search writes "Played a crucial role in enhancing our cybersecurity efforts ". On the other hand, the top reviewer of Weka writes "Open source, good for basic data mining use cases except for the visualization results". Elastic Search is most compared with Faiss, Milvus, Azure Search, Pinecone and Amazon Kendra, whereas Weka is most compared with KNIME, IBM SPSS Statistics, IBM SPSS Modeler, Oracle Advanced Analytics and SAS Analytics. See our Elastic Search vs. Weka report.
We monitor all Indexing and Search reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
