We performed a comparison between Elastic Search and Palantir Foundry based on real PeerSpot user reviews.
Find out in this report how the two Cloud Data Integration solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."We had many reasons to implement Elasticsearch for search term solutions. Elasticsearch products provide enterprise landscape support for different areas of the company."
"The observability is the best available because it provides granular insights that identify reasons for defects."
"It is stable."
"The tool's stability and performance are good."
"The most valuable features are the detection and correlation features."
"The solution has great scalability."
"The special text processing features in this solution are very important for me."
"The most valuable features of Elastic Enterprise Search are it's cloud-ready and we do a lot of infrastructure as code. By using ELK, we're able to deploy the solution as part of our ISC deployment."
"It's scalable."
"The solution offers very good end-to-end capabilities."
"The ease of use is my favorite feature. We're able to build different models and projects or combine different projects to build one use case."
"It is easy to map out a workflow and run trigger-based scripts without having to deploy to another server."
"Encapsulates all the components without the requirement to integrate or check compatibility."
"The data lineage is great."
"The virtualization tool is useful."
"The solution provides an end-to-end integrated tech stack that takes care of all utility/infrastructure topics for you."
"Could have more open source tools and testing."
"Elastic Enterprise Search could improve the report templates."
"There are some features lacking in ELK Elasticsearch."
"The reports could improve."
"I would rate the stability a seven out of ten. We faced a few issues."
"It should be easier to use. It has been getting better because many functions are pre-defined, but it still needs improvement."
"The UI point of view is not very powerful because it is dependent on Kibana."
"We'd like to see more integration in the future, especially around service desks or other ITSM tools."
"Compared to other hyperscalers, Palantir Foundry is complex and not so user-intuitive."
"It would be helpful to build applications based on Azure functions or web apps in Palantir Foundry."
"The data lineage was challenging. It's hard to track data from the sources as it moves through stages. Informatica EDC can easily capture and report it because it talks to the metadata. This is generated across those various staging points."
"The solution could use more online documentation for new users."
"There is not a wide user base for the solution's online documentation so it is sometimes difficult to find answers."
"The solution's visualization and analysis could be improved."
"It requires a lot of manual work and is very time-consuming to get to a functional point."
"The workflow could be improved."
Elastic Search is ranked 9th in Cloud Data Integration with 59 reviews while Palantir Foundry is ranked 12th in Cloud Data Integration with 14 reviews. Elastic Search is rated 8.2, while Palantir Foundry 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 Palantir Foundry writes "The data visualization is fantastic and the security is excellent". Elastic Search is most compared with Faiss, Milvus, Pinecone, Azure Search and Amazon Kendra, whereas Palantir Foundry is most compared with Azure Data Factory, Palantir Gotham, SAP Data Services, AWS Glue and Denodo. See our Elastic Search vs. Palantir Foundry report.
See our list of best Cloud Data Integration vendors.
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