intro
A vector database stores and indexes vector embeddings to facilitate vector-based searches. In this blog, we explore the Pinecone vector database appliance.
These days, vector databases are everywhere—they facilitate searches through vector embeddings for a similarity-based search as well as support various “vanilla” database capabilities, such as CRUD queries and scaling.
It’s true there are a variety of vector databases you can choose from—heck, even MariaDB is coming up with a version of its own —but in this blog, we’re exclusively focusing on one: the Pinecone vector database.
What is the Pinecone Vector Database?
Pinecone is a well-known cloud-based vector database appliance that offers various benefits and features for its users:
For Pinecone users, all of these benefits come into one appliance through a single vector-based search appliance.
Pinecone Vector Database Use Cases
Pinecone is often the preferred vector database for data professionals due to its ability to store data as numerical vectors and the ability to perform a vector similarity comparison. If Google Trends is to be trusted, we can clearly see that developers prefer using the Pinecone vector database as opposed to its competitors like the Facebook vector database search appliance (FAISS), Chroma, or Weaviate:
Factors related to the use case of the database have a say in that:
Is the Pinecone Vector Database Right for You?
With all these benefits and use cases, you may be facing numerous questions — and rightly so. The primary question you’d most likely be asking yourself is “Is this database a fit for my use case?” and well, it depends. It depends on multiple factors:
There are a couple of problems in this sphere — it’s easy to have a big vector-based data set, but may be hard to determine whether Pinecone fits your use case. To do that, keep in mind that the primary use case of Pinecone is to improve something based on existing data.
Think of it as sort of a classifier — feed Pinecone some data (e.g. spam letters), then let AI perform its magic using some machine learning and build a spam detector on it. Got the point?
Combining the Pinecone Vector Database with SQL Clients
Great! Now that you understand what Pinecone offers and what its database does, time to work on your databases, too. After all, you chose Pinecone because you’ve had vectors to work with, right?
The thing is, Pinecone is not the only vector database that you will encounter — MariaDB vectors are a thing, PostgreSQL or TimescaleDB users will make use of pgvector, and there are numerous other examples too.
Each of those databases, no matter if they’re used as vector databases or not, will come with their own challenges and problems. Some of those problems can only be solved by experienced DBAs, and what if you don’t have one by your side? Well, you can always turn to SQL clients like DbVisualizer!
DbVisualizer is the preferred SQL client for the world’s most prominent data professionals, and with long-time users from Volkswagen, Netflix, Spotify, and others, one can be certain that DbVisualizer can indeed solve most of our most pressing issues.
To access the list of databases supported by DbVisualizer, head over to Tools and select Drivers:
To add a new connection to DbVisualizer, find the database you find yourself using, double-click on it, and fill in the connection details. Once done, it will appear in the connection list (in my case, I have three database management systems — MySQL, MariaDB, and PostgreSQL — already set up as you can see below):
Once set up, you can start working with DbVisualizer. Its extensive features will help you from day one. For example, have you ever wanted to extend certain permissions to users? Do that with the SQL Commander Permissions tab found in the Tool Properties window:
Given that DbVisualizer offers support for more than 50 of the most popular data sources, an extensive feature set is a must. Having said that, you may not need to use all of the features available within DbVisualizer, but its SQL editor, permissions, and other things will surely come in handy for anyone using it.
Give it a spin today free for 21 days, and until next time.
Summary
Pinecone is a cloud-based vector database appliance that combines vector search with AI. It has extensive features, however, its use may not be for everyone. Those using “vanilla” database management systems may make use of SQL clients and editors like DbVisualizer — regardless of your decision in this realm, we hope this blog educated you on the available choices, and until next time.
FAQ
What is the Pinecone vector database?
Pinecone provides a vector database appliance combining vector search with AI. Its use cases are similar to classifier use cases where you have a data set, “feed” that data set to a vector database, and act on the obtained results.
Where can I learn more about vector databases and other database topics?
You can learn more about various database management systems, including vector databases, in various blogs such as the one provided by TheTable, as well as by listening to conference talks, attending seminars/webinars or workshops, reading books, or subscribing to YouTube channels like Database Dive and the like.
Is the Pinecone the only choice in the vector database market?
No — as far as vector databases are concerned, the Pinecone database is one of many choices. It’s a powerful choice, yes — but that doesn’t mean that it’s only one. There are many other choices available for you, and to make a proper decision, research the market, weigh your use case against a list of choices that you came up with, and make an informed decision.
