Azure AI Search vs. Coveo Relevance Cloud

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Azure AI Search
Score 7.9 out of 10
N/A
Azure AI Search (formerly Azure Cognitive Search) is enterprise search as a service, from Microsoft.
$0.10
Per Hour
Coveo Relevance Cloud
Score 7.1 out of 10
N/A
Coveo is an enterprise search technology which can index data on disparate cloud systems making it easier to retrieve. It has integrated plug-ins for Salesforce.com, Sitecore CEP, and Microsoft Outlook and SharePoint.
$600
per month
Pricing
Azure AI SearchCoveo Relevance Cloud
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
Base
$600
per month
Pro
$1,320
per month
Offerings
Pricing Offerings
Azure AI SearchCoveo Relevance Cloud
Free Trial
NoYes
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeOptional
Additional Details
More Pricing Information
Community Pulse
Azure AI SearchCoveo Relevance Cloud
Best Alternatives
Azure AI SearchCoveo Relevance Cloud
Small Businesses
Yext
Yext
Score 8.9 out of 10
Yext
Yext
Score 8.9 out of 10
Medium-sized Companies
Guru
Guru
Score 9.5 out of 10
Guru
Guru
Score 9.5 out of 10
Enterprises
Guru
Guru
Score 9.5 out of 10
Guru
Guru
Score 9.5 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Azure AI SearchCoveo Relevance Cloud
Likelihood to Recommend
7.0
(0 ratings)
10.0
(0 ratings)
Likelihood to Renew
-
(0 ratings)
6.6
(0 ratings)
User Testimonials
Azure AI SearchCoveo Relevance Cloud
Likelihood to Recommend
If you have a medium amount of data (2GB - 2.4TB), high-security concerns, and search is a key requirement in your single-tenant application then Azure Search likely has you covered. If you have a small amount of data per tenant (EG, about 2GB), have low-security concerns, and a multi-tenant application where search is a key requirement, then Azure Search would likely be a good choice - though you would need to implement your own concept of sharding and managing across potentially multiple Azure Search instances. If you can reflect your would-be indexes in Azure Search by depositing the data in columns in a SQL table and just index it for full-text search - and that still fits your requirements - it's probably better to start with SQL Database then scale up to Azure Search when you need the advanced features like ranking or cognitive abilities.
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Coveo Relevance Cloud is a great solution to implement into Salesforce to provide Knowledge-Centered Support, Enhancements to a Customer Community, to provide sales aids, or to complement your customized app in Salesforce.
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Pros
  • Incredibly robust back-end infrastructure.
  • Streamlined integration into Microsoft's Azure Cloud.
  • From a user standpoint, it lets the customer easily access their data and provide useful search tips.
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  • Good library of connectors to enterprise repositories including MS SharePoint, Exchange, Confluence. OOTB using the Open Connector API administrators were fairly easily be able to index content repositories.
  • Good security integration with existing repositories.
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Cons
  • Like virtually all Azure services, it has first-class treatment for .Net as the developer platform of choice, but largely ignores other options. While there is a first-party Python SDK, there are only community packages for other languages like Ruby and Node. Might be a game of roulette for those to be kept up-to-date. This might make it a non-starter for some teams that don't want to do the work to integrate with the REST API directly.
  • In my opinion, partitions inside of Azure Search don't count as data segregation for customers in a multi-tenant app, so any application where you have many customers with high-security concerns, Azure Search is probably a non-starter.
  • To elaborate on the multi-tenant issue: Azure Search's approach to pricing is pretty steep. While there is a free tier for small applications (50MB of content or less) the first paid tier is about 14x more expensive than the first SQL Database tier that supports full-text search. For many applications, it makes a lot more economic sense to just run some LIKE or CONTAINS queries on columns in a table rather than going with Azure Search.
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  • Coveo does its job but is lacking.
  • The results displayed by Coveo are not always relevant.
  • The results displayed by Coveo are not sorted, nor is there an option to sort.
  • The results displayed by Coveo are not location-specific, so results not relevant to my area or country gets shown.
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Likelihood to Renew
No answers on this topic
We still have many clients which have custom search implementations supported by Coveo which crawl their Sitecore instances. From that perspective, I'm very likely to use it again. One of the main drawbacks I have heard is that Coveo is relatively expensive. The size of your project budget may have a greater influence on your decision to use Coveo if the custom features are not must-haves for your organization
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Alternatives Considered
Azure Search is a competitor against Google's own AI autosuggest a feature. We went with Azure because our network security folks found it to be more robust from a security standpoint, which is incredibly important when you have proprietary manufacturing information. Additionally, we're a Microsoft shop so it plugged into our cloud hosting package and client facing OS.
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No answers on this topic
Return on Investment
  • Service cannot be downgrade or upgrade after creation
  • Good tool provide maximum ROI
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  • Quick to find things in a massive database when needed.
  • Results need to be more concise - sometimes we spend more time looking for the right file than if we were to just search amongst our own networks instead.
  • Coveo is not always the most useful but does its job when general information is needed.
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