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 pretty resilient."
"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."
"It provides good access capabilities to various platforms."
"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 solution's initial setup is straightforward."
"The search functionality time has been reduced to a few milliseconds."
"Search is really powerful."
"The solution has good security features. I have been happy with the dashboards and interface."
"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 UI is very nice, and performance wise it's quite good too."
"The most valuable features are the data store and the X-pack extension."
"A nonstructured database that can manage large amounts of nonstructured data."
"The forced merge and forced resonate features reduce the data size increasing reliability."
"The most valuable feature of Elastic Enterprise Search is user behavior analysis."
"They should add an API for third-party vendors, like a security operating center or reporting system, that would be a big improvement."
"The pricing is room for improvement."
"Adding items to Azure Search using its .NET APIs sometimes throws exceptions."
"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."
"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."
"Better dashboards or a better configuration system would be very good."
"Elastic Search needs to improve its technical support. It should be customer-friendly and have good support."
"Dashboards could be more flexible, and it would be nice to provide more drill-down capabilities."
"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)."
"There are challenges with performance management and scalability."
"Its licensing needs to be improved. They don't offer a perpetual license. They want to know how many nodes you will be using, and they ask for an annual subscription. Otherwise, they don't give you permission to use it. Our customers are generally military or police departments or customers without connection to the internet. Therefore, this model is not suitable for us. This subscription-based model is not the best for OEM vendors. Another annoying thing about Elasticsearch is its roadmap. We are developing something, and then they say, "Okay. We have removed that feature in this release," and when we are adapting to that release, they say, "Okay. We have removed that one as well." We don't know what they will remove in the next version. They are not looking for backward compatibility from the customers' perspective. They just remove a feature and say, "Okay. We've removed this one." In terms of new features, it should have an ODBC driver so that you can search and integrate this product with existing BI tools and reporting tools. Currently, you need to go for third parties, such as CData, in order to achieve this. ODBC driver is the most important feature required. Its Community Edition does not have security features. For example, you cannot authenticate with a username and password. It should have security features. They might have put it in the latest release."
"There is another solution I'm testing which has a 500 record limit when you do a search on Elastic Enterprise Search. That's the only area in which I'm not sure whether it's a limitation on our end in terms of knowledge or a technical limitation from Elastic Enterprise Search. There is another solution we are looking at that rides on Elastic Enterprise Search. And the limit is for any sort of records that you're doing or data analysis you're trying to do, you can only extract 500 records at a time. I know the open-source nature has a lot of limitations, Otherwise, Elastic Enterprise Search is a fantastic solution and I'd recommend it to anyone."
"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.