Pay as you grow

Our pricing is built around vector dimensions stored and queried, and different SLA-tiers have different prices per dimension. The exact calculation can be found in the FAQ below.
(not inclusive of discounts and taxes).

Vector Dimensions [?]
Data Objects
Monthly Queries
SLA Tier
High Availability
Your estimated price
$ 25 /mo

Pick your plan

Our pricing is designed to give you all the capabilities to build and test your applications for free. When you are ready to move to production, simply pick a plan that best suits your needs.

Sandbox

Free

  • Round robin region: AWS, Azure, GCP
  • 30 days lifetime
  • Community support
  • Single AZ

Standard

from

$ 25 /mo

  • $0.050 per 1M vector dimensions stored or queried per month
  • Round robin region: AWS, Azure, GCP
  • ∞ lifetime (until terminated)
  • Hibernation after 1 hour
  • Monitoring
  • Public Slack
  • Severity 1 - max 1h Severity 2 max 4h Severity 3 Severity 3 max 1bd
  • Multi AZ
  • HA optional

Enterprise

from

$ 135 /mo

  • $0.100 per 1M vector dimensions stored or queried per month
  • AWS, Azure, GCP
  • ∞ lifetime (until terminated)
  • Hibernation after 8 hours
  • Monitoring
  • SeMI Slack or Teams / Email
  • Severity 1 - max 1h
    Severity 2 - max 4h
    Severity 3 - max 1bd
  • Multi AZ
  • HA optional

Business Critical

from

$ 450 /mo

  • $0.175 per 1M vector dimensions stored or queried per month
  • AWS, Azure, GCP
  • ∞ lifetime (until terminated)
  • Always on
  • Monitoring
  • SeMI Slack or Teams / Email
  • Severity 1 - max 1h
    Severity 2 - max 4h
    Severity 3 - max 1bd
  • Multi AZ
  • HA optional

Frequently asked questions

Let us help answer the most common questions you might have.

Why do you price per vector dimension?

In Weaviate, you can attach a vector embedding to a data object. A vector embedding can have an x-amount of dimensions. Some vectors have a lot of embeddings (sometimes more than 10k), some just a few (e.g., 90). The more vector dimensions you store, the more infrastructure is needed to optimize and maintain performance, this is the reason why we calculate with individual dimensions. We believe it's the fairest and most accurate price to give you the best experience.

What's the Weaviate pricing formula?

You pay for the total amount of embedding dimensions stored per data object and per data object queried. For example, if you have a 100-dimensional embedding and you store 1k documents that you query 1k times per month. You pay for 200k dimensions.

(stored objects + objects queried) * embedding dimension size * SLA tier price per dimension

Is there a difference between Weaviate open source and the Weaviate version used by the WCS?

No, the Weaviate Cloud Service (WCS) is a different solution using the same code as Weaviate open-source. The difference is the WCS itself (i.e., SaaS) and different SLA types (opposed to the open-source BSD3 license).

Is there a discount for non-profits, startups, or students?

​Yes, please reach out to us at hello+discount@semi.technology.​

​Is the Weaviate Cloud Service SOC2 compliment?

Not yet; we are currently in the process of becoming SOC2 compliant. Feel free to email us for a status update on hello+soc2@semi.technology.​

What is Hibernation?

​Hibernation ​is a process where a cluster goes down (i.e., "hybernates") while retaining your data after a given period. This is ideal for research or development purposes; when the service endpoints are used again, the service comes back up with a short time delay.

​What is round-robin provisioning?​

​If your SLA tier contains round-robin provisioning, the Weaviate Cloud Service will provision on Amazon Web Services (AWS), Google Cloud Platform (GCP), ​or Microsoft Azure where enough resources are available.

Do I pay for data objects without embeddings?

​No, storage of data objects without vector embeddings is on us.​

​W​hich Weaviate modules​ are available?​

​Weaviate modules based on inference APIs are automatically integrated in the cloud service. These modules currently include Hugging Face Inference and OpenAI's embeddings end-points.​

Can I store data from different models with different embedding sizes?

Yes

​My use case fluctuates in the number of data objects stored per month, how do you calculate the total number of objects per month?

​We take the median number of vectors per month measured per hour.

What if I have an unexpected ​usage spike?

Usage spikes are -almost- always a good sign! Your Weaviate-powered app or platform is being actively used, and we don't want your bill to be in the way of your success. Spikes are analyzed at the end of the month, and occasional ones are on us.​

Who is behind Weaviate?​

​The company behind Weaviate is SeMI Technologies. They run the Cloud Service and maintain the open source software.​