Azure Search vs. ELK Elasticsearch

As of April 2019, 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 7 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 "Provides enterprise landscape support for different areas of the company". Azure Search is most compared with ELK Elasticsearch, Solr and Amazon AWS CloudSearch. ELK Elasticsearch is most compared with Azure Search, Solr and Amazon AWS CloudSearch. See our Azure Search vs. ELK Elasticsearch report.
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Azure Search Logo
3,310 views|2,028 comparisons
ELK Elasticsearch Logo
3,966 views|1,927 comparisons
Most Helpful Review
Find out what your peers are saying about Azure Search vs. ELK Elasticsearch and other solutions. Updated: March 2019.
332,644 professionals have used our research since 2012.
Quotes From Members

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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We had many reasons to implement Elasticsearch for search term solutions. Elasticsearch products provide enterprise landscape support for different areas of the company.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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We see the need for some improvements with Elasticsearch. We would like the Elasticsearch package to include training lessons for our staff.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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report
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332,644 professionals have used our research since 2012.
Ranking
2nd
out of 10 in Search as a Service
Views
3,310
Comparisons
2,028
Reviews
2
Average Words per Review
503
Avg. Rating
9.0
1st
out of 10 in Search as a Service
Views
3,966
Comparisons
1,927
Reviews
6
Average Words per Review
311
Avg. Rating
7.8
Top Comparisons
Compared 62% of the time.
Compared 26% of the time.
Compared 70% of the time.
Compared 12% of the time.
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Microsoft
Elastic
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.
Offer
Learn more about Azure Search
Learn more about ELK Elasticsearch
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
Find out what your peers are saying about Azure Search vs. ELK Elasticsearch and other solutions. Updated: March 2019.
332,644 professionals have used our research since 2012.
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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