Chroma DB Hosting | Vector Database for AI & RAG on GPU – B2BHostingClub

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Plans of Dedicated & GPU Servers for Chroma DB

We offer cost-effective dedicated servers with NVMe disk and NVIDIA GPU optimized servers for Chroma DB Hosting.

Express Dedicated Server - NVMe

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  • 32GB RAM
  • 4-Core E3-1230v3 @3.30 GHz
  • 120GB SSD + 1TB NVMe + 1TB SATA
  • 100Mbps-1Gbps Bandwidth
  • OS : Windows / Linux
  • 1 Dedicated IPv4 IP
  • No Setup Fee

Basic Dedicated Server - NVMe

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  • 64GB RAM
  • 8-Core E5-2667v4 @3.20 GHz
  • 120GB SSD + 2 x 1TB NVMe + 2TB SATA
  • 100Mbps-1Gbps Bandwidth
  • OS : Windows / Linux
  • 1 Dedicated IPv4 IP
  • No Setup Fee

Professional Dedicated Server - NVMe

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  • 128GB RAM
  • 16-Core Dual E5-2667v4 @3.20 GHz
  • 120GB SSD + 2TB NVMe + 4TB SATA
  • 100Mbps-1Gbps Bandwidth
  • OS : Windows / Linux
  • 1 Dedicated IPv4 IP
  • No Setup Fee

Advanced GPU Dedicated Server - A4000

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  • 12GB RAM
  • GPU: Nvidia Quadro RTX A4000
  • Dual 12-Core E5-2697v2
  • 240GB SSD + 2TB SSD
  • 100Mbps-1Gbps
  • OS: Linux / Windows 10/11
  • Single GPU Specifications:
  • Microarchitecture: Ampere
  • CUDA Cores: 6144
  • Tensor Cores: 192
  • GPU Memory: 16GB GDDR6
  • FP32 Performance: 19.2 TFLOPS

Advanced GPU Dedicated Server - A5000

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  • 128GB RAM
  • GPU: Nvidia Quadro RTX A5000
  • Dual 12-Core E5-2697v2
  • 240GB SSD + 2TB SSD
  • 100Mbps-1Gbps
  • OS: Linux / Windows 10/11
  • Single GPU Specifications:
  • Microarchitecture: Ampere
  • CUDA Cores: 8192
  • Tensor Cores: 256
  • GPU Memory: 24GB GDDR6
  • FP32 Performance: 27.8 TFLOPS

Enterprise GPU Dedicated Server - RTX A6000

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  • 256GB RAM
  • GPU: Nvidia Quadro RTX A6000
  • Dual 18-Core E5-2697v4
  • 240GB SSD + 2TB NVMe + 8TB SATA
  • 100Mbps-1Gbps
  • OS: Linux / Windows 10/11
  • Single GPU Specifications:
  • Microarchitecture: Ampere
  • CUDA Cores: 10,752
  • Tensor Cores: 336
  • GPU Memory: 48GB GDDR6
  • FP32 Performance: 38.71 TFLOPS

Enterprise GPU Dedicated Server - RTX 4090

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  • 256GB RAM
  • GPU: GeForce RTX 4090
  • Dual 18-Core E5-2697v4
  • 240GB SSD + 2TB NVMe + 8TB SATA
  • 100Mbps-1Gbps
  • OS: Linux / Windows 10/11
  • Single GPU Specifications:
  • Microarchitecture: Ada Lovelace
  • CUDA Cores: 16,384
  • Tensor Cores: 512
  • GPU Memory: 24 GB GDDR6X
  • FP32 Performance: 82.6 TFLOPS

Enterprise GPU Dedicated Server - A100(80GB)

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  • 256GB RAM
  • GPU: Nvidia A100
  • Dual 18-Core E5-2697v4
  • 240GB SSD + 2TB NVMe + 8TB SATA
  • 100Mbps-1Gbps
  • OS: Windows / Linux
  • Single GPU Microarchitecture: Ampere
  • CUDA Cores: 6912
  • Tensor Cores: 432
  • GPU Memory: 80GB HBM2e
  • FP32 Performance: 19.5 TFLOPS

Key Factors for Choosing a GPU for ChromaDB

When you are choosing GPU rental servers for ChromaDB, the following factors should be considered.

Compute Capability

Higher CUDA cores and tensor cores speed up operations like matrix multiplications.

Memory Size

Larger memory is essential for handling large embeddings and big datasets.

Memory Bandwidth

Handling many simultaneous queries or searches benefits from higher memory bandwidth and parallel processing power.

Embedding Size and Model Complexity

If you're generating embeddings with large language models (LLMs) or image models, you’ll need a powerful GPU.

Frequently asked questions

ChromaDB is an open-source vector database designed to efficiently store and query vector embeddings, which are numerical representations of data. It’s particularly useful in AI and machine learning applications that involve searching, filtering, or retrieving data based on semantic similarity. ChromaDB powers tasks like natural language search, recommendation systems, and more.
1. It’s lightweight and optimized specifically for modern ML applications.
2. Supports integration with Python tools and popular ML frameworks.
3. Designed for ease of use without compromising on performance for large-scale workloads.
Chroma DB is free and open source under the Apache 2.0 License. Pricing depends on the deployment option.
Chroma DB is a vector database system that allows you to store, retrieve, and manage embeddings. It can be used in Python or JavaScript with the chromadb library for local use, or connected to a remote server running Chroma.
Chroma DB, an open-source vector database tailored for AI applications, stands out for its scalability, ease of use, and robust support for machine learning tasks. This powerful database specializes in handling high-dimensional data like text embeddings efficiently.
Pinecone is a superb option for real-time search and scalability, whereas Chroma's open-source status and flexible query features offer versatility for a wide range of applications. ChromaDB scalability and open-source nature makes it a great fit for large scale AI applications.
Milvus is more suitable for large-scale, distributed environments where the flexibility of indexing and support for large datasets are key. On the other hand, Chroma shines in scenarios requiring real-time, low-latency search capabilities.

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