Algolia NeuralSearch™ pricing: how much is Algolia NeuralSearch™ costing exactly?
Algolia NeuralSearch™ vs Elasticsearch vs Solr
“Ultra fast”, “Super easy to implement” and “Easy, fast and relevant installation” are the key factors for which developers consider Algolia NeuralSearch™; while “Powerful API”, “Excellent Search Engine” and “Open Source” are the main reasons Elasticsearch or Solr is favored.
Out of the box relevancy: Algolia NeuralSearch™ wins
Elasticsearch (and Solr), or more exactly Lucene engine, is a great tool for big data analysis, but it is very difficult to achieve great relevance with it in WordPress research.
You can try adding logic on top of Elasticsearch or trying to rearrange the results of some queries, but it’s a tedious job that still needs to be sorted out.
Algolia NeuralSearch™ on the other hand focuses on very good relevance with minimal configuration. While not optimal for all use cases, it makes it particularly suitable for WordPress searching.
Open source: Solr wins
Algolia NeuralSearch™ is a black box, their software is proprietary and no one officially knows what their engine look like behind the scene.
This is inconvenient compared to Apache Solr and Elasticsearch, both being Open source (respectively Apache-license and SSPL license).
The main drawback of proprietary is to be locked-in to a provider: what will happen if you cannot afford anymore to pay for Algolia’s service?
Well, there is a good news for you: WPSOLR can run you current WordPress search with al three engines, which means you can just reindex your data in WPSOLR and instantly switch from Algolia NeuralSearch™ to Elasticsearch or Solr (or the other way round).
Of course, you would loose the out of the box relevancy of Algolia NeuralSearch™, but nothing prevents you from tuning your new index to your liking and get as close from Algolia’s quality as you want.
Analytics: Algolia NeuralSearch™ wins
Algolia NeuralSearch™ is pretty much out of reach when considering reporting and Analytics.
Out of the box, Algolia NeuralSearch™ provides not only Analytics report on your indexes and queries, but also let you act on your results to improve your results. For instance, you can find which queries yield no results to prevent visitors bounce. But also one can reorder search results query by query to display some results on top based on arbitrary reasons, like advertising or best sales.
Algolia analytic summary
Algolia NeuralSearch™ analytic searches
Algolia NeuralSearch™ analytic searches without results
Algolia NeuralSearch™ analytic filters
On this subject, Apache Solr delivers absolutely nothing.
And Elasticsearch provides very nice reporting tools, but mostly oriented to multi-dimentional analysis, like data-mining security logs in search for patterns. Search analytics is pretty much left empty.
NLP (Natural Language processing): Algolia NeuralSearch™ is an AI search
As a vector search, Algolia NeuralSearch™ is built with NLP features we are now used to with ChatGPT and other Open-source models.
Algolia NeuralSearch™ model is proprietary, with speed as the #1 goal. All queries are in ms, whatever the volume.
Furthermore, vectorizing texts in vectors is done at great speed inside Algolia’s infrastructure, which guarantees a good quality of service even in rush hours.
Manage your own Algolia NeuralSearch™ indexes
Create and delete indexes with one click.
Automatically install the index configuration, facets, searched fields and settings.
Choose your data
Choose post types, taxonomies, and custom fields to search.
Manage custom field types, and conversion errors.
Choose among several indexes.
Useful for multi-languages, or testing.
Click on one button to index, re-index, or delete your data.
Choose Incremental or full reindexing.
Index in real-time, or not.
Index by batches, and select the batch size.
Show debugging informations for troubleshooting.
Index what you need
Choose post types and taxonomies to index, re-index, or delete.