Azure Cognitive Search vs. Elasticsearch

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Azure Cognitive Search
Score 7.0 out of 10
N/A
Azure Cognitive Search (formerly Azure Search) is enterprise search as a service, from Microsoft.
$0.10
Per Hour
Elasticsearch
Score 8.2 out of 10
N/A
Elasticsearch is an enterprise search tool from Elastic in Mountain View, California.
$16
per month
Pricing
Azure Cognitive SearchElasticsearch
Editions & Modules
Basic
$0.101
Per Hour
Standard S1
$0.336
Per Hour
Standard S2
$1.344
Per Hour
Standard S3
$2.688
Per Hour
Standard
$16.00
per month
Gold
$19.00
per month
Platinum
$22.00
per month
Enterprise
Contact Sales
Offerings
Pricing Offerings
Azure Cognitive SearchElasticsearch
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Azure Cognitive SearchElasticsearch
Considered Both Products
Azure Cognitive Search
Chose Azure Cognitive Search
As I've mentioned, the biggest competitor to Azure Search is actually Azure SQL Database. It doesn't have as many features, but it's more economical and most .Net applications will have one already. As long as you can arrive at a schema and ranking strategy, it's a "good …
Elasticsearch

No answer on this topic

Top Pros
Top Cons
User Ratings
Azure Cognitive SearchElasticsearch
Likelihood to Recommend
8.2
(2 ratings)
9.0
(45 ratings)
Likelihood to Renew
-
(0 ratings)
10.0
(1 ratings)
Usability
-
(0 ratings)
10.0
(1 ratings)
Support Rating
-
(0 ratings)
7.8
(18 ratings)
Implementation Rating
-
(0 ratings)
9.0
(2 ratings)
User Testimonials
Azure Cognitive SearchElasticsearch
Likelihood to Recommend
Microsoft
Incredibly robust software for an enterprise organization to plug into their application. If you have a full development resource team at your disposal, this is great software and I highly recommend it. Largely, however, you won't be able to use this prior to the enterprise level. It's just too complicated and cumbersome of a product.
Read full review
Elastic
Elasticsearch is a really scalable solution that can fit a lot of needs, but the bigger and/or those needs become, the more understanding & infrastructure you will need for your instance to be running correctly. Elasticsearch is not problem-free - you can get yourself in a lot of trouble if you are not following good practices and/or if are not managing the cluster correctly. Licensing is a big decision point here as Elasticsearch is a middleware component - be sure to read the licensing agreement of the version you want to try before you commit to it. Same goes for long-term support - be sure to keep yourself in the know for this aspect you may end up stuck with an unpatched version for years.
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Pros
Microsoft
  • Azure Search provides a fully-managed service for loading, indexing, and querying content.
  • Azure Search has an easy C# SDK that allows you to implement loading and retrieving data from the service very easy. Any developer with some Microsoft experience should feel immediate familiarity.
  • Azure Search has a robust set of abilities around slicing and presenting the data during a search, such as narrowing by geospatial data and providing an auto-complete capabilities via "Suggesters".
  • Azure Search has one-of-a-kind "Cognitive Search" capabilities that enable running AI algorithms over data to enrich it before it is stored into the service. For example, one could automatically do a sentiment analysis when ingesting the data and store that as one of the searchable fields on the content.
Read full review
Elastic
  • As I mentioned before, Elasticsearch's flexible data model is unparalleled. You can nest fields as deeply as you want, have as many fields as you want, but whatever you want in those fields (as long as it stays the same type), and all of it will be searchable and you don't need to even declare a schema beforehand!
  • Elastic, the company behind Elasticsearch, is super strong financially and they have a great team of devs and product managers working on Elasticsearch. When I first started using ES 3 years ago, I was 90% impressed and knew it would be a good fit. 3 years later, I am 200% impressed and blown away by how far it has come and gotten even better. If there are features that are missing or you don't think it's fast enough right now, I bet it'll be suitable next year because the team behind it is so dang fast!
  • Elasticsearch is really, really stable. It takes a lot to bring down a cluster. It's self-balancing algorithms, leader-election system, self-healing properties are state of the art. We've never seen network failures or hard-drive corruption or CPU bugs bring down an ES cluster.
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Cons
Microsoft
  • It's an enterprise level product so you need to have the budget for it.
  • Challenging-to-impossible for a non-technical administrator to implement.
  • It further locks you into Microsoft's ecosystem and doesn't play well with non-Microsoft software. Depending on your point of view, this can be a pro or a con.
Read full review
Elastic
  • Joining data requires duplicate de-normalized documents that make parent child relationships. It is hard and requires a lot of synchronizations
  • Tracking errors in the data in the logs can be hard, and sometimes recurring errors blow up the error logs
  • Schema changes require complete reindexing of an index
Read full review
Likelihood to Renew
Microsoft
No answers on this topic
Elastic
We're pretty heavily invested in ElasticSearch at this point, and there aren't any obvious negatives that would make us reconsider this decision.
Read full review
Usability
Microsoft
No answers on this topic
Elastic
To get started with Elasticsearch, you don't have to get very involved in configuring what really is an incredibly complex system under the hood. You simply install the package, run the service, and you're immediately able to begin using it. You don't need to learn any sort of query language to add data to Elasticsearch or perform some basic searching. If you're used to any sort of RESTful API, getting started with Elasticsearch is a breeze. If you've never interacted with a RESTful API directly, the journey may be a little more bumpy. Overall, though, it's incredibly simple to use for what it's doing under the covers.
Read full review
Support Rating
Microsoft
No answers on this topic
Elastic
We've only used it as an opensource tooling. We did not purchase any additional support to roll out the elasticsearch software. When rolling out the application on our platform we've used the documentation which was available online. During our test phases we did not experience any bugs or issues so we did not rely on support at all.
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Implementation Rating
Microsoft
No answers on this topic
Elastic
Do not mix data and master roles. Dedicate at least 3 nodes just for Master
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Alternatives Considered
Microsoft
As I've mentioned, the biggest competitor to Azure Search is actually Azure SQL Database. It doesn't have as many features, but it's more economical and most .Net applications will have one already. As long as you can arrive at a schema and ranking strategy, it's a "good enough" solution. There are a variety of search technologies (Lucene, Solr, Elasticsearch) that implement a search service. Some of them are even open source, though I would only say "free" if you do not value your time. They most likely need to be hosted via Container (or VM if you're old school), so you're incurring DevOps costs to not only set them up but monitor and maintain them yourself.
If you're already on AWS, there is almost no reason to use Azure Search. Unless you're already multi-cloud, desperately need the cognitive abilities, and don't mind a potential performance hit from looking across datacenters (hey, it could happen), you should probably just use Amazon CloudSearch.
Read full review
Elastic
As far as we are concerned, Elasticsearch is the gold standard and we have barely evaluated any alternatives. You could consider it an alternative to a relational or NoSQL database, so in cases where those suffice, you don't need Elasticsearch. But if you want powerful text-based search capabilities across large data sets, Elasticsearch is the way to go.
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Return on Investment
Microsoft
  • Our internal market research illustrates that users are finding their desired information faster on account of autosuggest.
  • Time spent on checkout page (for conversions) is significantly decreased.
  • Clicks required on checkout page (for conversions) is significantly decreased.
Read full review
Elastic
  • We have had great luck with implementing Elasticsearch for our search and analytics use cases.
  • While the operational burden is not minimal, operating a cluster of servers, using a custom query language, writing Elasticsearch-specific bulk insert code, the performance and the relative operational ease of Elasticsearch are unparalleled.
  • We've easily saved hundreds of thousands of dollars implementing Elasticsearch vs. RDBMS vs. other no-SQL solutions for our specific set of problems.
Read full review