Apache Solr vs. Perplexity

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

Perplexity is helpful when you want auto-code generation for day-to-day problem scenarios such as Powershell script to accomplish a task, Code to invoke a REST API, Class generation from JSON/XML data, etc. It is also helpful when you want to correct or optimize code that you have self-written. Perplexity might not be best suited for scenarios when you need 100% accuracy without your self-verification of correctness.

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)

• Searching across the web
• Programming
• Diversity of answers

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

• Pictures generation could be better, other AI tools are better
• Creation of presentations
• Enterprise version for handling confidential (company) data

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 think it is very good; some minor tweaks might be helpful.

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

I think they both do well. I use ChatGPT for some pre-created GPTs. So because I use them for different functions, it's hard to compare them head-to-head. I also use an Abacus, which I like a lot. Overall, they are all good, but I have different use cases for each one.

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

• Faster content generation
• Brainstorming
• coming up with new ideas
• solving numerical problems
• Analytic and deep thinking skills

Incentivized