Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
VectorDB is a compact Python library designed for the effective storage and retrieval of text by employing techniques such as chunking, embedding, and vector search. It features a user-friendly interface that simplifies the processes of saving, searching, and managing text data alongside its associated metadata, making it particularly suited for scenarios where low latency is crucial. The application of vector search and embedding techniques is vital for leveraging large language models, as they facilitate the swift and precise retrieval of pertinent information from extensive datasets. By transforming text into high-dimensional vector representations, these methods enable rapid comparisons and searches, even when handling vast numbers of documents. This capability significantly reduces the time required to identify the most relevant information compared to conventional text-based search approaches. Moreover, the use of embeddings captures the underlying semantic meaning of the text, thereby enhancing the quality of search outcomes and supporting more sophisticated tasks in natural language processing. Consequently, VectorDB stands out as a powerful tool that can greatly streamline the handling of textual information in various applications.
Description
Searching and analyzing structured data is easy; however, over 80% of generated data is unstructured, requiring a different approach. Machine learning converts unstructured data into high-dimensional vectors of numerical values, which makes it possible to find patterns or relationships within that data type. Unfortunately, traditional databases were never meant to store vectors or embeddings and can not meet unstructured data's scalability and performance requirements.
Zilliz Cloud is a cloud-native vector database that stores, indexes, and searches for billions of embedding vectors to power enterprise-grade similarity search, recommender systems, anomaly detection, and more.
Zilliz Cloud, built on the popular open-source vector database Milvus, allows for easy integration with vectorizers from OpenAI, Cohere, HuggingFace, and other popular models. Purpose-built to solve the challenge of managing billions of embeddings, Zilliz Cloud makes it easy to build applications for scale.
API Access
Has API
No
API Access
Has API
Yes
Integrations
Amazon Web Services (AWS)
No
Azure Marketplace
No
ChatGPT
No
ChatGPT Plus
No
ChatGPT Pro
No
Cohere
No
Coral
No
Google Cloud Platform
No
HoneyHive
No
Hugging Face
No
Integrations
Amazon Web Services (AWS)
Yes
Azure Marketplace
Yes
ChatGPT
Yes
ChatGPT Plus
Yes
ChatGPT Pro
Yes
Cohere
Yes
Coral
Yes
Google Cloud Platform
Yes
HoneyHive
Yes
Hugging Face
Yes
Pricing Details
Free
Free Trial
No
Free Version
Yes
Pricing Details
$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
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
Yes
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
Yes
Live Rep (24/7)
Yes
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
No
In Person
Yes
Vendor Details
Company Name
VectorDB
Country
United States
Website
vectordb.com
Vendor Details
Company Name
Zilliz
Founded
2017
Country
United States
Website
zilliz.com
Product Features
Product Features
Database
Backup and Recovery
Yes
Creation / Development
No
Data Migration
Yes
Data Replication
No
Data Search
Yes
Data Security
Yes
Database Conversion
No
Mobile Access
No
Monitoring
No
NOSQL
No
Performance Analysis
No
Queries
Yes
Relational Interface
No
Virtualization
No