Amazon CloudSearch vs. Apache Solr

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

Very effective for end-user searching applications and for generating search results. Also very well suited to those looking for high reliability and performance. If [you're doing] fuzzy searching or if you are working on a smaller end-user application or an internal application that does not require high performance and flexible/adapting searching then it may not be necessary to use Solr.

Incentivized

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

Incentivized

• Faceted navigation and field collapsing/grouping : filtering and quick results were what we needed for our websites. Our customers needed to have this functionalities for good and efficient results.
• We tested them with our customers' registered searches (they received all new goods matching with their registered searches by emails and/or mobile push). Results were incredible by comparison with our old system (old MySQL requests).
• Note : we didn't put all our data in Solr. Just what we need for searching uses. Other data stayed in our MySQL database.
• Auto-suggest : our old auto-suggest wasn't performing well. With Apache Solr, our new one was worked really well ! The suggestions came quickly and suggestions were good.
• We also extended auto-suggestion with geo-spatial data and it worked well.
• Hit highlighting : we used this functionality and we didn't have problem and nasty surprise.
• Keep all data status during data upgrading (see next details for improvements)

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

Incentivized

• Ease of use -- this is not always the easier platform to configure.
• Developer Community -- There are not a whole lot of folks out there that understand this stuff so finding talent is difficult.
• Drupal 8 -- We've been frustrated with slow development on APIs for Drupal 8 integration.

Incentivized

It takes some time to deploy and currectly maintein it. And also, to learn how to use and integrate in the enviroment as well. Once you get theses steps done, it usability is very simple, and almost of the time it don't require no further attention on it. Even for maintence, if you deploy it on a cluster mode, it is very reliable and easy to take one host down.

Incentivized

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

We switched from search indexes stored in MySQL to soar and it's made a world of difference for our growing businesses. The relational databases are very poor for handling the complex data searches require and Solr delivered all the tools we need to get the performance our end users are demanding.

Incentivized

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

Incentivized

• It's enabled us to deliver fast, relevant search results on our new website. The site is still in beta and being actively developed so our complete ROI is still unknown.
• It integrates very well with Drupal so it has saved us from having to develop a custom solution.

Incentivized