Create a Vector Database With Open-Source
Vector databases are especially important in AI, but they are used for many other applications as well. Allowing for very quick and accurate indexing using AI embeddings that have been trained on contextual data, vector databases have a great role in our modern day tech. Learn how to create a vector-store database using open-source AI embeddings for absolutely free!
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Language
- English
Topic
- Artificial Intelligence
Enrollment Count
- 220
Skills You Will Learn
- Artificial Intelligence, Data Science, Python
Offered By
- IBMSkillsNetwork
Estimated Effort
- 2 hours
Platform
- SkillsNetwork
Last Update
- November 19, 2025
A Look at the Project Ahead
So what exactly are vector databases?
Vector databases are like smart organizers for information. They are important because they help us find things quickly and accurately. Imagine you have a big collection of pictures, and you want to find all the pictures of dogs. Instead of going through each picture one by one, a vector database can analyze the unique features of the images, like the shape of the ears or the color of the fur. This is possible through what we call "Embeddings", which are a way to measure those features. It then creates special codes called vectors that represent those features. So when you search for "dog," the database compares your search with all the vectors it has and finds the pictures that are most like dogs. This saves a lot of time and effort!
But that's not all! Vector databases can also help us with other things, like finding recommendations. Let's say you're listening to music on a streaming platform and you really like a song. The platform can use a vector database to analyze the characteristics of that song, like the rhythm or the melody. Then, it can compare it to other songs in its library and find similar ones that you might enjoy. So, vector databases help us organize and discover things in a clever and efficient way, whether it's finding pictures or suggesting awesome songs!
In this project you will learn how to create your own vector database using open-source tools. By the end of this guided project, you will know:
- What vector databases are and how they are constructed
- What embeddings are, and their role in vector databases
- How to choose the right embeddings for your project
- How to build and use your own vector database
What You'll Need
However, don't worry if you don't have much experience with the above. This project will explain each step along the way, and you may learn as-you-need along the way.
IBM Skills Network Labs environment also comes with many technical requisites pre-installed to save the hassle of setting everything up, so we won't be dealing with any environment issues.

Language
- English
Topic
- Artificial Intelligence
Enrollment Count
- 220
Skills You Will Learn
- Artificial Intelligence, Data Science, Python
Offered By
- IBMSkillsNetwork
Estimated Effort
- 2 hours
Platform
- SkillsNetwork
Last Update
- November 19, 2025
Instructors
Efkan Serhat Goktepe
Developer | Architect
Efkan is a 4th year student in Computer Science at University of Toronto. Efkan is currently working at IBM as a Software Architect. Contact: efkan@ibm.com.
Read moreContributors
Joseph Santarcangelo
Senior Data Scientist at IBM
Joseph has a Ph.D. in Electrical Engineering, his research focused on using machine learning, signal processing, and computer vision to determine how videos impact human cognition. Joseph has been working for IBM since he completed his PhD.
Read moreVicky Kuo
Data Scientist
I believe that success isn't just about individual milestones, but also about uplifting and encouraging others to reach their potential. This is why I'm passionate about combining my technical background with my eagerness to help people overcome technological hurdles and accelerate growth. When I’m not on the job, I love hiking with my two dogs or relaxing in a coffee shop. There's nothing better than having an insightful conversation over coffee, or even better, some volunteer work! Please feel free to reach out to me on LinkedIn.
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