We performed a comparison between Elastic Search and OpenText IDOL based on real PeerSpot user reviews.
Find out what your peers are saying about Elastic, IBM, OpenText and others in Indexing and Search."The ability to aggregate log and machine data into a searchable index reduces time to identify and isolate issues for an application. Saves time in triage and incident response by eliminating manual steps to access and parse logs on separate systems, within large infrastructure footprints."
"The most valuable feature of Elastic Enterprise Search is user behavior analysis."
"Dashboard is very customizable."
"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."
"The observability is the best available because it provides granular insights that identify reasons for defects."
"The forced merge and forced resonate features reduce the data size increasing reliability."
"We had many reasons to implement Elasticsearch for search term solutions. Elasticsearch products provide enterprise landscape support for different areas of the company."
"I like how it allows us to connect to Kafka and get this data in a document format very easily. Elasticsearch is very fast when you do text-based searches of documents. That area is very good, and the search is very good."
"IDOL has several important visual analytics, like face recognition and object detection and recognition."
"Elastic Search needs to improve authentication. It also needs to work on the Kibana visualization dashboard."
"There is an index issue in which the data starts to crash as it increases."
"Machine learning on search needs improvement."
"The solution's integration and configuration are not easy. Not many people know exactly what to do."
"There are a lot of manual steps on the operating system. It could be simplified in the user interface."
"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 is hard to learn and understand because it is a very big platform. This is the main reason why we still have nothing in production. We have to learn some things before we get there."
"Ratio aggregation is not supported in this solution."
"There is room for improvement in some very important capabilities in visual analytics. They have been focusing on improving the face recognition algorithm. The accuracy of object detection could be improved as well and I know they are working on that at the moment."
Elastic Search is ranked 1st in Indexing and Search with 59 reviews while OpenText IDOL is ranked 3rd in Indexing and Search with 5 reviews. Elastic Search is rated 8.2, while OpenText IDOL is rated 8.4. The top reviewer of Elastic Search writes "Played a crucial role in enhancing our cybersecurity efforts ". On the other hand, the top reviewer of OpenText IDOL writes "Scales linearly and vertically; primarily used in AI". Elastic Search is most compared with Faiss, Milvus, Pinecone, Azure Search and Sinequa, whereas OpenText IDOL is most compared with Lucene.
See our list of best Indexing and Search vendors.
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.
