Apache Solr is an open-source enterprise search server.
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Pinecone
Score 8.8 out of 10
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Pinecone is a fully managed vector database that makes it easy to add vector search to production applications. It combines state-of-the-art vector search libraries, advanced features such as filtering, and distributed infrastructure to provide high performance and reliability at any scale.
$0.07
per hour
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Apache Solr
Pinecone
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$0.01
per hour
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Apache Solr
Pinecone
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No
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Yes
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No
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No setup fee
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Community Pulse
Apache Solr
Pinecone
Features
Apache Solr
Pinecone
Vector Database
Comparison of Vector Database features of Product A and Product B
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.
Similarity search and ranking are fundamental capabilities, and Pinecone just has this nailed. Almost every application, especially those that talk to LLMs, can use this feature, and there is no reason to reinvent it or use anything more complicated or "full stack" than Pinecone. Pinecone is a powerful tool in this space.
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.
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.
Pinecone has come a long way (we have been using it for years). While the tooling used to have some rough edges, I can't really complain these days.
Migrating an entire database from one AWS zone to another basically required a full data dump and reload. That could be improved. I have not tried AWS=>GCP=>Azure replications/migrations, but suspect they are not yet well supported, and that would be helpful.
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 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 will be a little less expensive and offer more customization and flexibility.
When our product had a primitive search, we were lambasted by users, and we embraced Pinecone to fill an urgent need for something better. Over the years, it has become a wired-in foundation for more than a few product features.
The money we didn't spend creating and maintaining something "like" Pinecone has been one of our best investments.
