We performed a comparison between Azure Search and Elastic Search based on real PeerSpot user reviews.
Find out in this report how the two Search as a Service solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The search functionality time has been reduced to a few milliseconds."
"The product is extremely configurable, allowing you to customize the search experience to suit your needs."
"Because all communication is done via the REST API, data is retrieved quickly in JSON format to reduce overhead and latency."
"Creates indexers to get data from different data sources."
"The product is pretty resilient."
"The amount of flexibility and agility is really assuring."
"The customer engagement was good."
"Azure Search is well-documented, making it easy to understand and implement."
"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."
"Implementing the main requirements regarding my support portal."
"The most valuable feature of Elastic Enterprise Search is the opportunity to search behind and between different logs."
"The most valuable features are the detection and correlation features."
"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."
"Search is really powerful."
"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."
"The AI-based attribute tagging is a valuable feature."
"They should add an API for third-party vendors, like a security operating center or reporting system, that would be a big improvement."
"Adding items to Azure Search using its .NET APIs sometimes throws exceptions."
"The pricing is room for improvement."
"For availability, expanding its use to all Azure datacenters would be helpful in increasing awareness and usage of the product."
"The solution's stability could be better."
"It would be good if the site found a better way to filter things based on subscription."
"The initial setup is not as easy as it should be."
"The after-hour services are slow."
"The one area that can use improvement is the automapping of fields."
"The solution's integration and configuration are not easy. Not many people know exactly what to do."
"Elastic Enterprise Search could improve the report templates."
"They could improve some of the platform's infrastructure management capabilities."
"There are potential improvements based on our client feedback, like unifying the licensing cost structure."
"This product could be improved with additional security, and the addition of support for machine learning devices."
"Kibana should be more friendly, especially when building dashboards."
"There are challenges with performance management and scalability."
Azure Search is ranked 6th in Search as a Service with 8 reviews while Elastic Search is ranked 1st in Search as a Service with 59 reviews. Azure Search is rated 7.4, while Elastic Search is rated 8.2. The top reviewer of Azure Search writes "Good performance for standard faceted search and full-text search". On the other hand, the top reviewer of Elastic Search writes "Played a crucial role in enhancing our cybersecurity efforts ". Azure Search is most compared with Amazon Kendra, Amazon Athena, Amazon AWS CloudSearch, Algolia and Solr, whereas Elastic Search is most compared with Faiss, Milvus, Pinecone, Amazon Kendra and Qdrant. See our Azure Search vs. Elastic Search report.
See our list of best Search as a Service vendors.
We monitor all Search as a Service 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.