Sold by: Code Creator
Deployed on AWS
Code Creator Weaviate Vector AI Server deploys Weaviate Community Edition on Ubuntu as a ready-to-launch self-hosted vector database for semantic search, RAG, embeddings storage, and AI application backends. It exposes REST on port 8080 and gRPC on port 50051, and supports secure API based access through official client libraries and standard Weaviate interfaces. Note: this AMI provides the server backend only, so customers should plan to connect using their own API calls, client libraries, or external applications. This product has charges associated with it for the provision and deployment of the application and AMI support.
Overview
Code Creator Weaviate Vector AI Server provides a fast way to launch a self-hosted Weaviate Community Edition environment on AWS without building the stack from scratch. This AMI is designed for teams that want a dedicated vector database server for semantic search, retrieval augmented generation, embeddings storage, knowledge search, and AI-driven application backends running on their own EC2 infrastructure. Weaviate supports REST, GraphQL, and gRPC-based interaction patterns, with official client libraries available for common programming languages.
This AMI is prebuilt for a simple first-boot experience on Ubuntu with Docker-based deployment, exposing the standard Weaviate service ports of 8080 for HTTP and 50051 for gRPC. It is a strong fit for developers, data teams, and businesses that want a production-ready foundation for vector search and AI retrieval workflows while retaining control over their own AWS environment.
Customers can use this server with their own applications, custom workflows, or supported Weaviate client libraries. Official Weaviate clients help abstract the underlying REST, GraphQL, and gRPC calls, making it easier to integrate the server into Python, JavaScript, Go, Java, and other developer environments. This product provides the Weaviate server backend only. A built-in browser GUI is not included with this AMI. Customers should expect to connect from their own local machine, workstation, or application environment using API requests, official client libraries, or their own software stack.
Highlights
- Ready to launch Weaviate CE on Ubuntu with secure first boot setup and persistent storage
- Built for vector search semantic search rag backends and self hosted AI retrieval workflows
- Includes REST on port 8080 and gRPC on port 50051 with API based access for modern client libraries and applications
Details
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Delivery option
64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
Ubuntu 24.04
Deployed on AWS
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Pricing
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Cost/hour |
|---|---|
t3.large Recommended | $0.03 |
g5.xlarge | $0.03 |
t3.2xlarge | $0.03 |
c7i-flex.16xlarge | $0.03 |
g5.8xlarge | $0.03 |
c7i-flex.4xlarge | $0.03 |
c7i-flex.2xlarge | $0.03 |
c7i-flex.8xlarge | $0.03 |
c7i.12xlarge | $0.03 |
t3.xlarge | $0.03 |
Dimensions summary
You pay by the hour for the EC2 instance type you run this server on. The 12 options map to different instance families and sizes, so your cost scales with the compute you pick. The t3 sizes (large, xlarge, 2xlarge) are general-purpose. The c7i-flex and c7i sizes (2xlarge through 16xlarge) target compute-heavy work. The g5 sizes (xlarge through 8xlarge) add GPU capacity for AI workloads. Larger sizes carry more CPU, memory, or GPU, and bill at a higher hourly rate. Billing tracks actual hours used, with no upfront commitment.
Top-of-mind questions for buyers
You pay for each hour the EC2 instance runs, billed by the type you select. Options span t3 general-purpose sizes, c7i-flex and c7i compute sizes, and g5 GPU sizes. Each instance carries a set amount of CPU, memory, or GPU. Its hourly rate reflects that capacity.
Software charges apply per hour while the instance runs. When you stop the instance, the hourly software charge stops accruing. Stopped instances may still incur underlying AWS storage fees for attached volumes, but the software meter tracks running time only. There is no upfront commitment.
The g5 sizes add GPU capacity for AI and vector workloads that benefit from GPU acceleration. The c7i-flex and c7i sizes target compute-heavy processing without GPUs. The t3 sizes handle general-purpose work. Match the instance family to your workload, since the hourly rate scales with the resources it provides.
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Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
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Similar products
Enterprise Vector Database Platform and Assurance Support Services sold as a Weaviate UNITS SKU that customer can flexibly use
The Weaviate SaaS Platform offers hassle-free deployment, hosting the vector database cluster within your AWS tenant and VPC. This end-to-end deployment includes the Weaviate Enterprise Terms (support) and Enterprise Service License Agreement, ensuring a comprehensive and supported SaaS experience for your organization.
This product has charges associated with it for seller support. Weaviate is an open-source vector database that enables developers to store, search, and manage data using AI powered vector embeddings for semantic search, recommendation, and generative AI applications.
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