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 solution's initial setup is straightforward."
"Because all communication is done via the REST API, data is retrieved quickly in JSON format to reduce overhead and latency."
"Azure Search is well-documented, making it easy to understand and implement."
"The search functionality time has been reduced to a few milliseconds."
"The product is pretty resilient."
"Offers a tremendous amount of flexibility and scalability when integrating with applications."
"The customer engagement was good."
"The amount of flexibility and agility is really assuring."
"The most valuable feature is the out of the box Kibana."
"The solution is quite scalable and this is one of its advantages."
"Implementing the main requirements regarding my support portal."
"It is easy to scale with the cluster node model."
"Helps us to store the data in key value pairs and, based on that, we can produce visualisations in Kibana."
"The products comes with REST APIs."
"The initial installation and setup were straightforward."
"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."
"It would be good if the site found a better way to filter things based on subscription."
"The pricing is room for improvement."
"They should add an API for third-party vendors, like a security operating center or reporting system, that would be a big improvement."
"The initial setup is not as easy as it should be."
"For SDKs, Azure Search currently offers solutions for .NET and Python. Additional platforms would be welcomed, especially native iOS and Android solutions for mobile development."
"The solution's stability could be better."
"For availability, expanding its use to all Azure datacenters would be helpful in increasing awareness and usage of the product."
"The after-hour services are slow."
"I would like to see more integration for the solution with different platforms."
"Elastic Search needs to improve authentication. It also needs to work on the Kibana visualization dashboard."
"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)."
"It should be easier to use. It has been getting better because many functions are pre-defined, but it still needs improvement."
"The reports could improve."
"The documentation regarding customization could be better."
"There is an index issue in which the data starts to crash as it increases."
"They should improve its documentation. Their official documentation is not very informative. They can also improve their technical support. They don't help you much with the customized stuff. They also need to add more visuals. Currently, they have line charts, bar charts, and things like that, and they can add more types of visuals. They should also improve the alerts. They are not very simple to use and are a bit complex. They could add more options to the alerting system."
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.