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."The initial installation and setup were straightforward."
"The most valuable features are the data store and the X-pack extension."
"The product is scalable with good performance."
"It is stable."
"The solution is stable and reliable."
"Elastic Enterprise Search is scalable. On a scale of one to 10, with one being not scalable and 10 being very scalable, I give Elastic Enterprise Search a 10."
"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."
"The flexibility and the support for diverse languages that it provides for searching the database are most valuable. We can use different languages to query the database."
"It is easy to map out a workflow and run trigger-based scripts without having to deploy to another server."
"The solution provides an end-to-end integrated tech stack that takes care of all utility/infrastructure topics for you."
"The AI engine that comes with Palantir Foundry is quite interesting."
"The data lineage is great."
"Palantir Foundry is a robust platform that has really strong plugin connectors and provides features for real-time integration."
"Live video sessions enhance the available documentation and allow you to ask questions directly."
"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's scalable."
"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."
"Elastic Enterprise Search could improve its SSL integration easier. We should not need to go to the back-end servers to do configuration, we should be able to do it on the GUI."
"Elastic Enterprise Search could improve the report templates."
"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)."
"It needs email notification, similar to what Logentries has. Because of the notification issue, we moved to Logentries, as it provides a simple way to receive notification whenever a server encounters an error or unexpected conditions (which we have defined using RegEx)."
"This product could be improved with additional security, and the addition of support for machine learning devices."
"Its licensing needs to be improved. They don't offer a perpetual license. They want to know how many nodes you will be using, and they ask for an annual subscription. Otherwise, they don't give you permission to use it. Our customers are generally military or police departments or customers without connection to the internet. Therefore, this model is not suitable for us. This subscription-based model is not the best for OEM vendors. Another annoying thing about Elasticsearch is its roadmap. We are developing something, and then they say, "Okay. We have removed that feature in this release," and when we are adapting to that release, they say, "Okay. We have removed that one as well." We don't know what they will remove in the next version. They are not looking for backward compatibility from the customers' perspective. They just remove a feature and say, "Okay. We've removed this one." In terms of new features, it should have an ODBC driver so that you can search and integrate this product with existing BI tools and reporting tools. Currently, you need to go for third parties, such as CData, in order to achieve this. ODBC driver is the most important feature required. Its Community Edition does not have security features. For example, you cannot authenticate with a username and password. It should have security features. They might have put it in the latest release."
"We have an issue with the volume of data that we can handle."
"If you want to create new models on specific data sets, computing that is quite costly."
"They do not have a data center in Europe, and we have lots of personally identifiable information in our dataset that needs to be hosted by a third-party data center like Amazon or Microsoft Azure."
"The frontend capabilities of Palantir Foundry could be improved."
"The solution could use more online documentation for new users."
"It would be helpful to build applications based on Azure functions or web apps in Palantir Foundry."
"There is not a wide user base for the solution's online documentation so it is sometimes difficult to find answers."
"Compared to other hyperscalers, Palantir Foundry is complex and not so user-intuitive."
"It requires a lot of manual work and is very time-consuming to get to a functional point."
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 Alteryx Designer. See our Elastic Search vs. Palantir Foundry report.
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