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 product is extremely configurable, allowing you to customize the search experience to suit your needs."
"The solution's initial setup is straightforward."
"The search functionality time has been reduced to a few milliseconds."
"The product is pretty resilient."
"The customer engagement was good."
"Because all communication is done via the REST API, data is retrieved quickly in JSON format to reduce overhead and latency."
"The amount of flexibility and agility is really assuring."
"Creates indexers to get data from different data sources."
"It's a stable solution and we have not had any issues."
"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."
"A nonstructured database that can manage large amounts of nonstructured data."
"It is highly valuable because of its simplicity in maintenance, where most tasks are handled for you, and it offers a plethora of built-in features."
"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 most valuable feature is the out of the box Kibana."
"It is stable."
"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."
"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."
"It would be good if the site found a better way to filter things based on subscription."
"The after-hour services are slow."
"For availability, expanding its use to all Azure datacenters would be helpful in increasing awareness and usage of the product."
"Adding items to Azure Search using its .NET APIs sometimes throws exceptions."
"The initial setup is not as easy as it should be."
"They should add an API for third-party vendors, like a security operating center or reporting system, that would be a big improvement."
"There are a lot of manual steps on the operating system. It could be simplified in the user interface."
"The reports could improve."
"We'd like more user-friendly integrations."
"I would like to be able to do correlations between multiple indexes."
"We see the need for some improvements with Elasticsearch. We would like the Elasticsearch package to include training lessons for our staff."
"The different applications need to be individually deployed."
"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."
"Both the graph feature and the reporting feature are a little bit lacking. The alerting also needs to be improved."
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, Solr and Algolia, whereas Elastic Search is most compared with Faiss, Milvus, Pinecone, Amazon Kendra and OpenText IDOL. 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.