Apache Solr is an open-source enterprise search server.
N/A
Searchspring
Score 9.0 out of 10
N/A
Searchspring headquartered in Denver offers intelligent site search for customer facing web pages and ecommerce, providing product discvoery tools, navigation viacategory page, and other features to improve site navigation.
In February 2020, Searchspring merged with Nextopia to expand its product capabilities, and customer base. Nextopia customers will continue to receive the same services, under the SearchSpring brand.
$599
per month
Pricing
Apache Solr
Searchspring
Editions & Modules
No answers on this topic
Essential
$599.00
per month
Advanced
$799.00
per month
Expert
$999.00
per month
Offerings
Pricing Offerings
Apache Solr
Searchspring
Free Trial
No
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
—
—
More Pricing Information
Community Pulse
Apache Solr
Searchspring
Considered Both Products
Apache Solr
Verified User
Anonymous
Chose Apache Solr
Apache Solr is a ready-to-use product addressing specific use cases such as keyword searches from a huge set of data documents.
We have considering AWS search and Elastic search but decide to go with Solr as we need high speed and flexible query, and so far it meets all our requirement so we still continue with Solr.
We tried to use both Elasticsearch and Swiftype with Drupal 8 but there are currently no good modules that integrate Drupal with those solutions. So Solr was really the only option for a Drupal 8 web site. It's not as easy to learn or use as Swiftype, but in the end I think it …
Before using Solr, we used a self-made search engine. Solr has helped us increase our capacity to serve our customers the results they are looking for easily without breaking down. Our previous platform was not dynamic enough to accommodate our growing traffic or smart enough …
Azure Search is not as mature as Apache Solr at this point. So the range of query flexibility is less than Solr. Also, when indexing content goes beyond 1 TB, it might become costly for Azure Search.
Between Solr and ElasticSearch, there is a constant struggle to pick the best one. ElasticSearch is part of ELK and ties in well with LogStash and Kibana which makes it great for logs and big data stuff. Add some logs and see which works best for your particular access methods …
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 …
Apache Solr in general stacks up very well to its competitors, it provides much of the same features and performance and has the benefits of being an open-source project with an active contributor base that works consistently and improves the platform. Depending on your setup …
We tryed to promote Redis as cache solution for application, in order to replace Apache Solr, but it won't go well. Redis best pratices requires some more computer resources. With Elastic Search, the use case was another, and don't compete with Apache Solr.
We reviewed multiple providers 5 years ago before making the switch to Search Spring. While I can't recall the providers we reviewed we have been very happy with Search Spring. We appreciate the transparency to their product roadmap and their acquisition of 4-Tell to improve …
Considering SearchSpring is the only software I've used like this, I don't really have a frame of reference to go against. I know that in relation to other integrations we have they are affordable and we get a good amount of actionable data from them to make incremental changes …
Nextopia’s features were on par or better than consideration set at a lower cost and with an easier implementation. Contract terms were also more favorable.
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.
SearchSpring has improved our conversion rate on our website in just the few weeks we've had them on the site. It is obvious that the improvements will continue over time with the incremental increases in traffic every week.
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)
Customize search results pages - ability to add banners or other visual creative for search results pages based on specific queries.
Easily badge products - set thumbnail badges to show specific messages on search results pages; allows for easy identification of items on sale, featured items, or items that may be eligible for free shipping.
Easily merchandise search results pages - can be done on a per-query basis.
Would like to see 4-Tell and Search Spring in one dashboard.
Dream: Using customer demographic data plus past purchases plus browsing history to recommend products (machine learning), ability to easily manually connect specific products that the algorithm may not catch, for example, earrings and necklaces in the same style, accessory type products, etc. We would want this to work so that relating a product to another automatically works in reverse (currently it has to be done for both items).
Ability to create custom landing page results that do not show "search results for ____" at the top
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.
We have a monthly phone call with our account manager, and she is available for calls in between as well. She has always been accessible. Working with her has been easy and she has provided training where needed. She is proactive in making sure we have everything we need and feel comfortable with the platform.
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.
We reviewed multiple providers 5 years ago before making the switch to Search Spring. While I can't recall the providers we reviewed we have been very happy with Search Spring. We appreciate the transparency to their product roadmap and their acquisition of 4-Tell to improve their product recommendations engine.
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.