Amazon CloudSearch vs Azure Search

• Really fast queries
• Good Reporting
• Reduce the cost of the server

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• 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.

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• Can take some time to implement
• The initial configuration can be tricky
• Takes some time to update the values

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• 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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• Positive Point - Reduced the server load
• Negative point - Not suitable for all queries
• Negative Point - Time to implement this feature

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• Azure Search enabled us to stand up a robust search capability with very few developer hours.
• The fully-managed service of Azure Search means we get low cost of management (EG, DevOps) going into the future, even though the cost of the service itself definitely reflects the time saved.
• Azure Search counts as a "Cognitive Service" for Microsoft Azure consumption and aligns our products with Microsoft's interests of driving an AI-first approach in the enterprise. Microsoft Partners, service and product companies alike, should be looking to align with this AI vision as it means favorable treatment from the Microsoft sales teams.

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