Azure Search vs. ELK Elasticsearch

Azure Search is ranked 2nd in Search as a Service with 2 reviews vs ELK Elasticsearch which is ranked 1st in Search as a Service with 6 reviews. The top reviewer of Azure Search writes "Offers a tremendous amount of flexibility and scalability when integrating with applications". The top reviewer of ELK Elasticsearch writes "Allows us to store data in key value pairs and produce visualisations in Kibana, but lack of email notification is problematic". Azure Search is most compared with ELK Elasticsearch, Solr and Amazon AWS CloudSearch. ELK Elasticsearch is most compared with Azure Search, Algolia and Amazon AWS CloudSearch. See our Azure Search vs. ELK Elasticsearch report.
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Quotes From Members Comparing Azure Search vs. ELK Elasticsearch

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
Pros
Offers a tremendous amount of flexibility and scalability when integrating with applications.The product is extremely configurable, allowing you to customize the search experience to suit your needs.Because all communication is done via the REST API, data is retrieved quickly in JSON format to reduce overhead and latency.​The search functionality time has been reduced to a few milliseconds.Creates indexers to get data from different data sources.

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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 ability to aggregate log and machine data into a searchable index reduces time to identify and isolate issues for an application. Saves time in triage and incident response by eliminating manual steps to access and parse logs on separate systems, within large infrastructure footprints.Helps us to store the data in key value pairs and, based on that, we can produce visualisations in Kibana.It helps us to analyse the logs based on the location, user, and other log parameters.It is easy to scale with the cluster node model.​Implementing the main requirements regarding my support portal​.X-Pack provides good features, like authorization and alerts.

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Cons
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.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.

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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).Performance improvement could come from skipping background refresh on search idle shards (which is already being addressed in the upcoming seventh version).Enterprise scaling of what have been essentially separate, free open source software (FOSS) products has been a challenge, but the folks at Elastic have published new add-ons (X-Pack and ECE) to help large companies grow ELK to required scales.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​).Machine learning on search needs improvement.

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Pricing and Cost Advice
​When telling people about the product, I always encourage them to set up a new service using the free pricing tier. This allows them to learn about the product and its capabilities in a risk-free environment. Depending on their needs, the free tier may be suitable for their projects, however enterprise applications will most likely required a higher, paid tier.For the actual costs, I encourage users to view the pricing page on the Azure site for details.​

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This is a free, open source software (FOSS) tool, which means no cost on the front-end. There are no free lunches in this world though. Technical skill to implement and support are costly on the back-end with ELK, whether you train/hire internally or go for premium services from Elastic.​The pricing and license model are clear: node-based model.ELK has been considered as an alternative to Splunk to reduce licensing costs.An X-Pack license is more affordable than Splunk.

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Avg. Rating
9.0
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3,237
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1,764
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7.8
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5.0
Top Comparisons
Compared 54% of the time.
Compared 22% of the time.
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Compared 57% of the time.
Compared 19% of the time.
See more ELK Elasticsearch competitors »
Compared 25% of the time.
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Overview
Azure Search is a search-as-a-service cloud solution that gives developers APIs and tools for adding a rich search experience over your data in web, mobile, and enterprise applications. Functionality is exposed through a simple REST API or .NET SDK that masks the inherent complexity of search technology. In addition to APIs, the Azure portal provides administration and prototyping support. Infrastructure and availability are managed by Microsoft.Elasticsearch is a distributed, JSON-based search and analytics engine designed for horizontal scalability, maximum reliability, and easy management. Elasticsearch lets you perform and combine many types of searches — structured, unstructured, geo, metric — any way you want.
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Sample Customers
XOMNI, Real Madrid C.F., Weichert Realtors, JLL, NAV CANADA, Medihoo, autoTrader Corporation, GjirafaHotelTonight, Perceivant, Docker, Green Man Gaming, Xoom, AutoScout24, TheLadders, Center for Open Science, Parleys, Tango
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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.

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