Likelihood to Recommend
If you have a dedicated developer who has the technical know-how to delve deep into Algolia's documentation to figure out what makes it tick, this is the product for you. Algolia's framework is extremely powerful, making search instantaneous and providing users with results at break-neck speeds. If all you need is great search, but you do not require a complex relevancy algorithm running it, Algolia will work well for you. The more complex your use case, the more expensive the product becomes.
Program Manager in Product ManagementHuman Resources Company, 11-50 employees
Solr spins up nicely and works effectively for small enterprise environments providing helpful mechanisms for fuzzy searches and facetted searching. For larger enterprises with complex business solutions you'll find the need to hire an expert Solr engineer to optimize the powerful platform to your needs.Internationalization is tricky with Solr and many hosting solutions may limit you to a latin character set.
- Algolia is brain-dead simple to set up. I've implemented search with Algolia in a dozen different ways now, and it never took me longer than a few minutes to get the functionality I want. With Algolia, the only challenge is designing your search UI -- if you don't want to use their baked in UI solutions.
- Results come back incredibly fast. I'm not sure how Algolia does it, but every keystroke I make in a search field returns new results instantly. It's hard to believe that I'm searching large datasets on a remote server when it works so fast.
- Very little customization is needed for 99% of use-cases. Algolia's out of the box setup works great, and it takes no prior knowledge to set up.
- Easy to get started with Apache Solr. Whether it is tackling a setup issue or trying to learn some of the more advanced features, there are plenty of resources to help you out and get you going.
- Performance. Apache Solr allows for a lot of custom tuning (if needed) and provides great out of the box performance for searching on large data sets.
- Maintenance. After setting up Solr in a production environment there are plenty of tools provided to help you maintain and update your application. Apache Solr comes with great fault tolerance built in and has proven to be very reliable.
Engineer in EngineeringComputer Software Company, 51-200 employees
- Algolia can be a bit complex -- for smaller companies or companies without many tech resources, it may be difficult to implement and use without the help of a third party
- Manually manipulating search results (for specific queries having listings show up first) is a bit difficult to do without custom developing that functionality
- These examples are due to the way we use Apache Solr. I think we have had the same problems with other NoSQL databases (but perhaps not the same solution). High data volumes of data and a lot of users were the causes.
- We have lot of classifications and lot of data for each classification. This gave us several problems:
- First: We couldn't keep all our data in Solr. Then we have all data in our MySQL DB and searching data in Solr. So we need to be sure to update and match the 2 databases in the same time.
- Second: We needed several load balanced Solr databases.
- Third: We needed to update all the databases and keep old data status.
- If I don't speak about problems due to our lack of experience, the main Solr problem came from frequency of updates vs validation of several database. We encountered several locks due to this (our ops team didn't want to use real clustering, so all DB weren't updated). Problem messages were not always clear and we several days to understand the problems.
Based on 2 answers
We did have one occurrence where we maxed out our plan and the service didn't respond well. This is probably a very common scenario and it took half a day to get things back to normal with slow response time. Price is also a consideration. If you are restrained in that sense you might want to dedicate the time to having your own setup from the get-go.
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Algolia at first seemed and proved to be the fastest compared to the other search engines. It is very easy to implement. Also, it had a 24x7 support which proved to be very useful. It is also useful for all types of clients weather it be organizations or individuals. It can also handle typos. It also focuses on features like API and SSL Security. Also, it is designed to search records, not pages. These were some of the reasons we went ahead with Algolia.
Analyst in Information TechnologyFinancial Services Company, 10,001+ employees
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.
Return on Investment
- It's too early to measure any increase in our transactions
- We have good customer feedback on the Algolia search function
- We are looking at other apps in development where we can also leverage the power of Algolia
C-Level Executive in Information TechnologyFinancial Services Company, 51-200 employees
- 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.
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