Azure AI Search vs. Lucidworks Fusion

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.

Incentivized

Very well suited for out of the box enterprise search applications.

• 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.

Incentivized

• Signals feature to boost search results helps search relevancy
• Business Rules feature for tuning search results
• Query pipeline design gives great flexibility in application development

• 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.

Incentivized

• Documentation can be improved

It is incredibly intuitive and so easy to use that business people can now complete functions that used to be limited to software developers only.

It has continued to improve over the years.

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.

Incentivized

IDOL seems to be a blackbox solution. Fusion is much more flexible with more features and options for developers to choose from.

• 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.

Incentivized

• Allowed us to move software developers from enterprise search to other customer focused applications due to built in signals processing and related popularity boosting out of the box.
• Enabled business experts to work directly with Fusion to influence search results and not be so dependent on developers.