Sold by: kCloudHubs LLC
Deployed on AWS
AWS Free Tier
This product has charges associated with it for seller support. Turbopuffer is a serverless vector and full-text search database that delivers fast, scalable, and cost-effective search for AI and enterprise applications. Built on object storage, it supports vector, keyword, and hybrid search with automatic scaling and low operational overhead.
Overview
Turbopuffer 2.4.0 on Ubuntu 26.04 with Free Maintenance Support by kCloud
Turbopuffer 2.4.0 on Ubuntu 26.04 is a serverless vector database and full-text search platform designed for AI applications, semantic search, retrieval-augmented generation (RAG), recommendation systems, and large-scale data retrieval workloads. It combines vector search, keyword search, and hybrid search capabilities while leveraging object storage for virtually unlimited scalability. This solution includes free maintenance support from kCloud and optional enterprise-grade support for production AI deployments.
Turbopuffer enables organizations to build intelligent search experiences without managing database infrastructure. Its serverless architecture automatically scales with workload demands, making it ideal for AI-powered applications, enterprise knowledge bases, document search platforms, and machine learning systems.
What Turbopuffer Does
Turbopuffer stores and indexes vector embeddings, structured metadata, and text content, allowing applications to perform semantic similarity search, full-text search, and hybrid retrieval. It helps developers build AI systems that can efficiently retrieve relevant information from large datasets while minimizing operational complexity.
Key Features
- Serverless vector database optimized for AI and machine learning applications.
- High-performance semantic search using vector embeddings.
- Full-text search and hybrid search capabilities in a unified platform.
- Automatic scaling without infrastructure management.
- Object storage-based architecture for cost-efficient data storage.
- Support for metadata filtering and advanced search queries.
Technical Highlights
- Turbopuffer 2.4.0 deployment on Ubuntu 26.04 LTS.
- Vector indexing and retrieval for large-scale AI workloads.
- Hybrid search combining semantic and keyword-based retrieval.
- Serverless architecture with automatic performance scaling.
- Designed for Retrieval-Augmented Generation (RAG) systems.
- API-driven integration with modern AI frameworks and applications.
AWS Marketplace Benefits
- Pre-configured deployment for rapid AI search infrastructure setup.
- Reduces operational overhead with serverless architecture.
- Accelerates development of AI-powered search and recommendation systems.
- Scalable storage and retrieval for growing datasets.
- Optimized for cloud-native machine learning and generative AI workloads.
Use Cases
- Retrieval-Augmented Generation (RAG) applications.
- Semantic document and knowledge base search.
- AI-powered recommendation engines.
- Enterprise search and information retrieval systems.
- Vector similarity search for machine learning applications.
- Hybrid search across structured and unstructured datasets.
Maintenance Support
kCloud provides free maintenance support for Turbopuffer 2.4.0 deployments, helping customers maintain reliable search infrastructure, optimize performance, and resolve configuration issues. Optional premium support is available for advanced architecture design, AI integration, scaling strategies, security hardening, and enterprise deployment requirements.
Why Choose This Solution?
Turbopuffer 2.4.0 on Ubuntu 26.04 delivers a modern, serverless approach to vector search and AI data retrieval. By combining semantic search, full-text search, and automatic scalability, it enables organizations to build powerful AI applications without the complexity of managing traditional search infrastructure. It is an excellent choice for businesses developing next-generation search, recommendation, and generative AI solutions.
Highlights
- Serverless vector database for AI and semantic search.
- Hybrid search combining vector and keyword retrieval.
- Scales automatically without infrastructure management.
Details
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Delivery method
Delivery option
64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
Ubuntu 26.04
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.
If you are an AWS Free Tier customer with a free plan, you are eligible to subscribe to this offer. You can use free credits to cover the cost of eligible AWS infrastructure. See AWS Free Tier for more details. If you created an AWS account before July 15th, 2025, and qualify for the Legacy AWS Free Tier, Amazon EC2 charges for Micro instances are free for up to 750 hours per month. See Legacy AWS Free Tier for more details.
Dimension | Cost/hour |
|---|---|
m4.large Recommended | $0.10 |
t2.micro | $0.001 |
t3.micro | $0.10 |
r3.large | $0.10 |
r4.large | $0.10 |
t3.large | $0.10 |
t2.large | $0.10 |
t3.medium | $0.10 |
t2.2xlarge | $0.10 |
t2.medium | $0.10 |
Dimensions summary
You pay by the hour for this software, and your rate depends on the EC2 instance type you run. The 21 options map to different AWS instance families and sizes. Burstable instances (t2 and t3) range from nano through 2xlarge, letting you match compute to lighter or heavier workloads. Compute-optimized (c3, c4, c5), general-purpose (m3, m4, m5), and memory-optimized (r3, r4, r5) families cover other performance needs. Larger sizes and more powerful families carry higher hourly rates. You run only the instance you select and pay for the hours you use.
Top-of-mind questions for buyers
You pay for the running time of the EC2 instance you launch, billed per hour. The rate bundles the software plus the compute resources of that instance type. Each instance size maps to a set amount of virtual CPUs and memory. You select one instance type per deployment.
The software rate meters running hours only. When you stop an instance, hourly software charges stop accruing. Underlying AWS storage fees for attached volumes may still apply while the instance is stopped, but the software license itself bills only for active running time.
Your hourly rate includes maintenance support from the vendor. This covers help with keeping the deployment running, such as updates and monitoring assistance. The support applies regardless of which instance type you choose. Underlying AWS infrastructure charges are billed separately by AWS.
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No Refund
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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.
Version release notes
Packaged with latest updates as of June/2026
Additional details
Usage instructions
Connect you your instance via SSH, the username is ubuntu. More info on SSH: https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/AccessingInstancesLinux.html - Run the following commands:
sudo su
cd /opt
source turbopuffer-env/bin/activate
pip show turbopuffer
python -c "import turbopuffer; print(turbopuffer.version)"
Support
Vendor support
Feel free to reach out anytime. Our support team is available 24x7 for assistance mail: meha@kcloudhubs.com
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
Similar products
This product has charges associated with it for seller support. TurboPuffer is a lightweight Python client designed for interacting with high-performance vector databases. It enables developers to store, search, and retrieve vector embeddings efficiently, making it useful for AI-powered applications like semantic search, recommendation systems, and machine learning workflows.
Milvus, the world most popular open-source vector database (42k+ GitHub stars), now offers an official fully managed service: Zilliz Cloud, built by the original Milvus team. Purpose-built for GenAI embedding workloads and trusted by 10,000+ organizations, Zilliz delivers hybrid search and sub-10 ms latency at billion-vector scale. Enjoy a monthly Free Tier (5GB storage, 2.5M vCUs) or try Serverless/Dedicated free for 30 days, cancel anytime.
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