Apache Solr vs. Elastic Enterprise Search

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.

Incentivized

Swiftype is excellent for e-commerce companies and especially the financial services sector where speed plays a major role in executing transactions. It is also very dynamic and customizable. It is very useful for electronics/travel reservations on e-commerce sites also. The only place it is inappropriate is when it comes to indexing a website in which case Google is slightly better, as I mentioned before. There is nothing much to complain about here in regards to the breadth of applications and analytics it offers.

Incentivized

• 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.

Incentivized

• It's very easy to implement. The documentation is great and you can be up and running very quickly.
• It's easy to configure. The web-based user interface makes it super simple to configure (i.e. customize search rankings, edit synonyms, etc.).
• Their support is very friendly and helpful. Whenever I had a question or couldn't figure something old, they were quick to help me out.

Incentivized

• 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.

• Swiftype does not have indexes ready to go. When you add a new website to the search set, it takes some time to index the website. This is something that is different from what Google does. Google in this particular aspect does a relatively better job.
• Swiftype is very expensive, this makes it difficult for smaller companies to afford.

Incentivized

Apache Solr is a ready-to-use product addressing specific use cases such as keyword searches from a huge set of data documents.

Incentivized

Google Search Appliance is no longer supported. Apache Solr is a popular, free open source solution, but it lacks a web crawler and is more difficult to configure and maintain.

Incentivized

• Improved response time in e-commerce websites.
• Developer's job is easier with Apache Solr in use.
• Customization in filtering and sorting is possible.

Incentivized

• It has a positive impact as it helps traders and other users to seamlessly use applications.
• It has a positive ROI and we would know the results in time to come.

Incentivized