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."Creates indexers to get data from different data sources."
"It provides good access capabilities to various platforms."
"The product is pretty resilient."
"The solution's initial setup is straightforward."
"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 product is extremely configurable, allowing you to customize the search experience to suit your needs."
"The amount of flexibility and agility is really assuring."
"The most valuable features are the detection and correlation features."
"The most valuable feature of the solution is its utility and usefulness."
"The solution offers good stability."
"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."
"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."
"The most valuable feature is the out of the box Kibana."
"Implementing the main requirements regarding my support portal."
"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."
"The after-hour services are slow."
"Adding items to Azure Search using its .NET APIs sometimes throws exceptions."
"The pricing is room for improvement."
"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 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."
"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."
"Elastic Enterprise Search could improve the report templates."
"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)."
"Elastic Enterprise Search's tech support is good but it could be improved."
"The one area that can use improvement is the automapping of fields."
"The price could be better. Kibana has some limitations in terms of the tablet to view event logs. I also have a high volume of data. On the initialization part, if you chose Kibana, you'll have some limitations. Kibana was primarily proposed as a log data reviewer to build applications to the viewer log data using Kibana. Then it became a virtualization tool, but it still has limitations from a developer's point of view."
"There are some features lacking in ELK Elasticsearch."
"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, 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.