Azure AI Search vs. OpenSearch

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.

Incentivized

OpenSearch Service presents a cost-effective pricing model, allowing users to pay solely for their usage without being burdened by minimum fees or upfront commitments. Its seamless integration with various AWS services enhances its adaptability for a wide range of data analysis requirements and also I love using it isn't it enough.

• 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.

Incentivized

• Gives us millisecond response times
• Mainly open-source
• Integration Seamlessly with AWS
• Has a very big community so problems are fixes sooner then later

• 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.

Incentivized

• Needs more descriptive documentation
• The UI feels a bit old
• Some functionality still doesn't work correctly

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.

Incentivized

Well as I said, Elastic is behind paywall now and managing OpenSearch through AWS is so seamless that we just love it. It gets updates faster we don't have to manage separate infra and many other settings to work with elastic search and some of the tools that it provides are better then them.

• Service cannot be downgrade or upgrade after creation
• Good tool provide maximum ROI

Incentivized

• Well we had 200 ms response times which decreased to 100ms while using OpenSearch
• Easy to use security plugins we dont need external IAM
• Super Easy Integration with many AWS Services such as kinsesi data stream and dynamoDB