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What is Zilliz Cloud?

While working with structured data is relatively straightforward, a significant majority—over 80%—of data generated today is unstructured, necessitating a different methodology. Machine learning plays a crucial role by transforming unstructured data into high-dimensional numerical vectors, which facilitates the discovery of underlying patterns and relationships within that data. However, conventional databases are not designed to handle vectors or embeddings, falling short in addressing the scalability and performance demands posed by unstructured data. Zilliz Cloud is a cutting-edge, cloud-native vector database that efficiently stores, indexes, and searches through billions of embedding vectors, enabling sophisticated enterprise-level applications like similarity search, recommendation systems, and anomaly detection. Built upon the widely-used open-source vector database Milvus, Zilliz Cloud seamlessly integrates with vectorizers from notable providers such as OpenAI, Cohere, and HuggingFace, among others. This dedicated platform is specifically engineered to tackle the complexities of managing vast numbers of embeddings, simplifying the process of developing scalable applications that can meet the needs of modern data challenges. Moreover, Zilliz Cloud not only enhances performance but also empowers organizations to harness the full potential of their unstructured data like never before.

What is Pinecone?

The AI Knowledge Platform offers a streamlined approach to developing high-performance vector search applications through its Pinecone Database, Inference, and Assistant. This fully managed and user-friendly database provides effortless scalability while eliminating infrastructure challenges. After creating vector embeddings, users can efficiently search and manage them within Pinecone, enabling semantic searches, recommendation systems, and other applications that depend on precise information retrieval. Even when dealing with billions of items, the platform ensures ultra-low query latency, delivering an exceptional user experience. Users can easily add, modify, or remove data with live index updates, ensuring immediate availability of their data. For enhanced relevance and speed, users can integrate vector search with metadata filters. Moreover, the API simplifies the process of launching, utilizing, and scaling vector search services while ensuring smooth and secure operation. This makes it an ideal choice for developers seeking to harness the power of advanced search capabilities.

Media

Media

Integrations Supported

Amazon Web Services (AWS)
Azure Marketplace
ChatGPT
ChatGPT Plus
ChatGPT Pro
Coral
Google Cloud Platform
HoneyHive
Hugging Face
OpenAI
PyTorch

Integrations Supported

Amazon Web Services (AWS)
Azure Marketplace
ChatGPT
ChatGPT Plus
ChatGPT Pro
Coral
Google Cloud Platform
HoneyHive
Hugging Face
OpenAI
AICosts.ai
Airtool
Databricks
Knolli
Lyzr
Prompt Security
Skott
Voxel51
troveGEN

API Availability

Has API

API Availability

Has API

Pricing Information

$0
Zilliz Cloud on AWS
Compute Unit (CU) - $0.259 / hour
Storage - $0.025 / GB per month

Zilliz Cloud on Google Cloud
Compute Unit (CU) - $0.215 / hour
Storage - $0.02 / GB per month
Free Trial Offered?

Pricing Information

Pricing not provided
Free Version

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
On-Site Training

Training Options

Documentation Hub
Webinars

Company Facts

Organization Name

Zilliz

Date Founded

2017

Company Location

United States

Company Website

zilliz.com

Company Facts

Organization Name

Pinecone

Date Founded

2019

Company Location

United States

Company Website

www.pinecone.io

Categories and Features

Anomaly Detection

Not specified

Context Engineering

Not specified

Database

Backup and Recovery
Data Migration
Data Search
Data Security
Queries

Vector Databases

Not specified

Categories and Features

AI Development

Not specified

AI Inference

Not specified

AI Memory Layers

Not specified

Context Engineering

Not specified

Semantic Search

Not specified

Vector Databases

Not specified

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