Director at a tech services company with 1-10 employees
Real User
Top 5
May 23, 2026
Our main use case for Supabase Vector is to use pgvector as the vector database solution to store our embeddings for large language model applications. A specific example of how I'm using Supabase Vector for our large language model application is when we are building the Retrieval Augmented Generation (RAG) pipeline for an education application for one of our clients. We used the client's training material to perform chunking and embedding generation, and then stored the embeddings into Supabase Vector. The major purpose of my use case with Supabase Vector is to store the embeddings.
Software Developer at a performing arts with 1-10 employees
Real User
Top 10
Apr 7, 2026
I'm using Supabase Vector for the Postgres part. I use their Postgres database as the main requirement for the product from my side. If I am building a small website or any product, I don't need to create a backend for that part and host it. I can use Supabase APIs, such as their connection string, and it functions as a BaaS, backend as a service.
I have wanted to delve into the backend process, which is just another whole different universe. Supabase Vector puts such an entire universe into a small planet and gives it to the front-end developer, making it really good. I use it as my database for authentication for real-time features and a lot of stuff. The tool is literally used for BaaS. If, as a solo developer, I want to start something of my own, and I do not have the resources to afford backend developers, or if I even want to learn about the backend, then Supabase Vector is a great replacement. I don't have to deploy the backend because it already comes as a deployed service on the tool's cloud. The main USP of Supabase Vector is that the API requests are not charged, so they are unlimited.
We use the product primarily to handle data models and API integrations. It simplifies security setup, API documentation generation, and database management.
Supabase Vector offers an efficient way to manage and query vector embeddings, catering to the needs of developers and data scientists seeking scalable solutions for vector-based data handling. Supabase Vector is designed to streamline the process of storing, managing, and querying vector embeddings, essential for applications like machine learning algorithms and personalized recommendations. Its intuitive API and integration capabilities make it a preferred choice for tech professionals...
Our main use case for Supabase Vector is to use pgvector as the vector database solution to store our embeddings for large language model applications. A specific example of how I'm using Supabase Vector for our large language model application is when we are building the Retrieval Augmented Generation (RAG) pipeline for an education application for one of our clients. We used the client's training material to perform chunking and embedding generation, and then stored the embeddings into Supabase Vector. The major purpose of my use case with Supabase Vector is to store the embeddings.
I'm using Supabase Vector for the Postgres part. I use their Postgres database as the main requirement for the product from my side. If I am building a small website or any product, I don't need to create a backend for that part and host it. I can use Supabase APIs, such as their connection string, and it functions as a BaaS, backend as a service.
I am exploring Supabase for my project on UMKM.
I have wanted to delve into the backend process, which is just another whole different universe. Supabase Vector puts such an entire universe into a small planet and gives it to the front-end developer, making it really good. I use it as my database for authentication for real-time features and a lot of stuff. The tool is literally used for BaaS. If, as a solo developer, I want to start something of my own, and I do not have the resources to afford backend developers, or if I even want to learn about the backend, then Supabase Vector is a great replacement. I don't have to deploy the backend because it already comes as a deployed service on the tool's cloud. The main USP of Supabase Vector is that the API requests are not charged, so they are unlimited.
We use the product primarily to handle data models and API integrations. It simplifies security setup, API documentation generation, and database management.