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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 Deeplake?

Deeplake is a GPU-native database and multimodal AI data runtime from Activeloop that helps developers build faster, more capable production AI agents. It is designed for the agentic era, where AI systems do not just query data occasionally but continuously create, retrieve, reason over, and update data during autonomous workflows. Deeplake brings together serverless Postgres, vector search, multimodal data lake functionality, analytical query performance, and GPU acceleration in one platform. The database is built to reduce the bottlenecks caused when AI models run on GPUs but data retrieval still depends on CPU-based systems and repeated data transfers. For agentic loops, Deeplake acts as a high-speed memory layer that helps agents retrieve context and act across rapid cycles. For physical AI, it supports data from robots, sensors, videos, 3D scans, and model artifacts in one searchable system. For generative media, it indexes content by meaning so teams can find images, video, audio, and other assets without depending only on manual folders or tags. Deeplake also supports vector database and RAG workflows, helping teams build applications that need scalable retrieval and context management. Its architecture is positioned around familiar database concepts, including Postgres-style access, while adding AI-optimized storage and GPU-speed execution. Organizations can deploy Deeplake in VPC environments and use it as part of secure enterprise AI infrastructure. With open-source momentum, SOC 2 Type II certification, multimodal support, and GPU-native performance, Deeplake gives AI teams a modern data foundation for agents, robotics, retrieval, training, and media intelligence.

Media

Media

Integrations Supported

Amazon Web Services (AWS)
ChatGPT
Google Cloud Platform
OpenAI
PyTorch
Activeloop
Amazon SageMaker
Azure Marketplace
ChatGPT Plus
ChatGPT Pro
Cohere
Coral
HoneyHive
Hugging Face
IBM watsonx.data
Java
Jupyter Notebook
LangChain
Milvus
TensorFlow

Integrations Supported

Amazon Web Services (AWS)
ChatGPT
Google Cloud Platform
OpenAI
PyTorch
Activeloop
Amazon SageMaker
Azure Marketplace
ChatGPT Plus
ChatGPT Pro
Cohere
Coral
HoneyHive
Hugging Face
IBM watsonx.data
Java
Jupyter Notebook
LangChain
Milvus
TensorFlow

API Availability

Has API

API Availability

Has API

Pricing Information

$0
Free Trial Offered?
Free Version

Pricing Information

$0
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

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
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Zilliz

Date Founded

2017

Company Location

United States

Company Website

zilliz.com

Company Facts

Organization Name

Activeloop

Date Founded

2018

Company Location

United States

Company Website

deeplake.ai/

Categories and Features

Database

Backup and Recovery
Creation / Development
Data Migration
Data Replication
Data Search
Data Security
Database Conversion
Mobile Access
Monitoring
NOSQL
Performance Analysis
Queries
Relational Interface
Virtualization

Categories and Features

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