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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 LanceDB?

LanceDB is a user-friendly, open-source database tailored specifically for artificial intelligence development. It boasts features like hyperscalable vector search and advanced retrieval capabilities designed for Retrieval-Augmented Generation (RAG), as well as the ability to handle streaming training data and perform interactive analyses on large AI datasets, positioning it as a robust foundation for AI applications. The installation process is remarkably quick, allowing for seamless integration with existing data and AI workflows. Functioning as an embedded database—similar to SQLite or DuckDB—LanceDB facilitates native object storage integration, enabling deployment in diverse environments and efficient scaling down when not in use. Whether used for rapid prototyping or extensive production needs, LanceDB delivers outstanding speed for search, analytics, and training with multimodal AI data. Moreover, several leading AI companies have efficiently indexed a vast array of vectors and large quantities of text, images, and videos at a cost significantly lower than that of other vector databases. In addition to basic embedding capabilities, LanceDB offers advanced features for filtering, selection, and streaming training data directly from object storage, maximizing GPU performance for superior results. This adaptability not only enhances its utility but also positions LanceDB as a formidable asset in the fast-changing domain of artificial intelligence, catering to the needs of various developers and researchers alike.

Media

Media

Integrations Supported

IBM watsonx.data
Amazon Web Services (AWS)
ChatGPT Plus
Hugging Face
Java
PyTorch

Integrations Supported

IBM watsonx.data
Airtable
Amazon S3
Azure Blob Storage
Cognee
Harvey AI
Midjourney
Python
Ray
Rust
SQLite
Spark
TypeScript
Vercel
pandas

API Availability

Has API

API Availability

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

$16.03 per month
Free Version

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
On-Site Training

Training Options

Documentation Hub

Company Facts

Organization Name

Zilliz

Date Founded

2017

Company Location

United States

Company Website

zilliz.com

Company Facts

Organization Name

LanceDB

Company Location

United States

Company Website

lancedb.com

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

Context Engineering

Not specified

Database

Not specified

Embedded Database

Not specified

Vector Databases

Not specified

Popular Alternatives

Popular Alternatives

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Embeddinghub

Featureform
Milvus Reviews & Ratings

Milvus

Zilliz