Azure AI Search (formerly Azure Cognitive Search) is enterprise search as a service, from Microsoft.
$0.10
Per Hour
IBM Watson Content Analytics
Score 8.0 out of 10
N/A
IBM Watson Content Analytics is an enterprise search option. This supersedes IBM's older offerings, IBM Omnifind and IBM Content Analytics and Enterprise Search.
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.
IBM Content Analytics is well suited for organizations with the resources to invest a significant amount of energy in an advanced analytics engine. The software improved the productivity of analysts and programmers. The software is not suitable for companies that just want Excel-type analyses or that lack the capabilities of doing advanced analytics.
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.
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.
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.
Perhaps the biggest advantage of IBM Watson Content Analytics is the IBM feel. I think IBM puts lots of resources into developing products that even sociologists can use. It's so easy, that to professionals wanting customized analysis, it might be kind of offensive. The drawback is that Content Analytics is not as fast as its competitors.
