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."Offers a tremendous amount of flexibility and scalability when integrating with applications."
"The amount of flexibility and agility is really assuring."
"Creates indexers to get data from different data sources."
"The product is pretty resilient."
"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."
"The customer engagement was good."
"The search functionality time has been reduced to a few milliseconds."
"Helps us to store the data in key value pairs and, based on that, we can produce visualisations in Kibana."
"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."
"X-Pack provides good features, like authorization and alerts."
"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 AI-based attribute tagging is a valuable feature."
"Logsign provides us with the capability to execute multiple queries according to our requirements. The indexing is very high, making it effective for storing and retrieving logs. The real-time analytics with Elastic benefits us due to the huge traffic volume in our organization, which reaches up to 60,000 requests per second. With logs of approximately 25 GB per day, manually analyzing traffic behavior, payloads, headers, user agents, and other details is impractical."
"The forced merge and forced resonate features reduce the data size increasing reliability."
"The solution is quite scalable and this is one of its advantages."
"It would be good if the site found a better way to filter things based on subscription."
"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."
"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 after-hour services are slow."
"Adding items to Azure Search using its .NET APIs sometimes throws exceptions."
"The pricing is room for improvement."
"The initial setup is not as easy as it should be."
"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)."
"The one area that can use improvement is the automapping of fields."
"I would like to see more integration for the solution with different platforms."
"The UI point of view is not very powerful because it is dependent on Kibana."
"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."
"The pricing of this product needs to be more clear because I cannot understand it when I review the website."
"The solution's integration and configuration are not easy. Not many people know exactly what to do."
"I don't see improvements at the moment. The current setup is working well for me, and I'm satisfied with it. Integrating with different platforms is also fine, and I'm not recommending any changes or enhancements right now."
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.