Pricing plans
Choose the Perfect Plan for Your Business Needs
Choose the Perfect Plan for Your Business Needs
If you encounter any issues, please reach out to us.
If you encounter any issues, please reach out to us.
If you encounter any issues, please reach out to us.
Free
1 CPU / 2 GB RAM
For demo and learning purposes
No HA guarantee
Free
1 CPU / 2 GB RAM
For demo and learning purposes
No HA guarantee
Free
1 CPU / 2 GB RAM
For demo and learning purposes
No HA guarantee
Enterprise
$0.2016/h for 2 CPUs / 8GB RAM
$0.2646/h for 2 CPUs / 16GB RAM
$0.5292/h for 4 CPUs / 32GB RAM
Enterprise
$0.2016/h for 2 CPUs / 8GB RAM
$0.2646/h for 2 CPUs / 16GB RAM
$0.5292/h for 4 CPUs / 32GB RAM
Enterprise
$0.2016/h for 2 CPUs / 8GB RAM
$0.2646/h for 2 CPUs / 16GB RAM
$0.5292/h for 4 CPUs / 32GB RAM
Frequently Asked Questions
Frequently Asked
Questions
You can find answers of common questions below
Can I try out PGVecto.rs Cloud without any initial investment?
Can I try out PGVecto.rs Cloud without any initial investment?
Can I try out PGVecto.rs Cloud without any initial investment?
How often will I be billed for using PGVecto.rs Cloud?
How often will I be billed for using PGVecto.rs Cloud?
How often will I be billed for using PGVecto.rs Cloud?
USER TESTIMONIALS
Showcase with PGVecto.rs
Trusted by Many Open Source Projects
Showcase with PGVecto.rs
Trusted by Many Open Source Projects
• Immich.app Developer from GitHub
pgvector has limited support for filtering; you generally have to query for the nearest rows and apply filters on that result set. This means its recall can be abysmal, and it makes it very difficult to improve search in the ways we want. pgvecto.rs doesn't have these limitations and can indeed provide as many results as requested for a set of filters. This allows for much more powerful search in a seamless way, including the ability to have infinite scroll.
mag e/acc
• From Twitter
I was using @modal_labs for getting embeddings, and @qdrant_engine
for vectors, then realised I need lots of filtering and switched to pgvecto.rs
• Immich.app Developer from GitHub
pgvector has limited support for filtering; you generally have to query for the nearest rows and apply filters on that result set. This means its recall can be abysmal, and it makes it very difficult to improve search in the ways we want. pgvecto.rs doesn't have these limitations and can indeed provide as many results as requested for a set of filters. This allows for much more powerful search in a seamless way, including the ability to have infinite scroll.
mag e/acc
• From Twitter
I was using @modal_labs for getting embeddings, and @qdrant_engine
for vectors, then realised I need lots of filtering and switched to pgvecto.rs
• Immich.app Developer from GitHub
pgvector has limited support for filtering; you generally have to query for the nearest rows and apply filters on that result set. This means its recall can be abysmal, and it makes it very difficult to improve search in the ways we want. pgvecto.rs doesn't have these limitations and can indeed provide as many results as requested for a set of filters. This allows for much more powerful search in a seamless way, including the ability to have infinite scroll.
mag e/acc
• From Twitter
I was using @modal_labs for getting embeddings, and @qdrant_engine
for vectors, then realised I need lots of filtering and switched to pgvecto.rs