Amazon CloudSearch vs. Inbenta Enterprise Search

Amazon Cloudsearch can be suitable for some queries that require fast data. For example, in our case, we used CloudSearch, in a tool called Global Search. That will search everything like names, emails and a lot of stuff in our application. If you want fast data and you have a simple query, Global Search isn't appropriate for you.

Incentivized

If you are looking for an enterprise search platform that offers an easy to use interface and if high performance is not really your priority, then I believe Inbenta Enterprise Search would fit your use case. For most other situations, I would recommend using a tried and tested search platform like Apache Solr.

Incentivized

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

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• Fairly easy to use interface.
• Quick to onboard new users, both in terms of access as well as training.
• The NLP-based semantic search feature is quite impressive.

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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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• It is a fairly new tool in the market, so not much market feedback exists for this. This made us apprehensive in using it.
• The documentation and online forums are bare minimum.
• Quite buggy when working with multiple sources.

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I didn't investigate the best alternatives to CloudSearch, but did help with implementing this feature in our application. But from what i tested and used - Cloudsearch is very fast to get queries. Some negative points can be the time to implement this and some configurations that can be tricky.

Incentivized

Apache Solr to Inbenta is like Java to Python. Apache Solr is powerful and handles complex search platforms well. Inbenta, on the other hand, is meant to be easy to use and does not lay too much emphasis on performance. If you are a small or medium business, Inbenta may suit your needs better. However, if you wish to manage a large and complex search platform, Solr is the way to go.

Incentivized

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

Incentivized

• Enabled our developers to quickly deploy changes to the search model.
• NLP-powered semantic search feedback provides good actionable insights.

Incentivized