Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Vald is a powerful and scalable distributed search engine designed for fast approximate nearest neighbor searches of dense vectors. Built on a Cloud-Native architecture, it leverages the rapid ANN Algorithm NGT to efficiently locate neighbors. With features like automatic vector indexing and index backup, Vald can handle searches across billions of feature vectors seamlessly. The platform is user-friendly, packed with features, and offers extensive customization options to meet various needs.
Unlike traditional graph systems that require locking during indexing, which can halt operations, Vald employs a distributed index graph, allowing it to maintain functionality even while indexing. Additionally, Vald provides a highly customizable Ingress/Egress filter that integrates smoothly with the gRPC interface. It is designed for horizontal scalability in both memory and CPU, accommodating different workload demands. Notably, Vald also supports automatic backup capabilities using Object Storage or Persistent Volume, ensuring reliable disaster recovery solutions for users. This combination of advanced features and flexibility makes Vald a standout choice for developers and organizations alike.
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
IBM watsonx.data
Yes
Java
Yes
Amazon Web Services (AWS)
No
Azure Marketplace
No
ChatGPT
No
ChatGPT Plus
No
ChatGPT Pro
No
Cohere
No
Coral
No
Docker
Yes
Integrations
IBM watsonx.data
Yes
Java
Yes
Amazon Web Services (AWS)
Yes
Azure Marketplace
Yes
ChatGPT
Yes
ChatGPT Plus
Yes
ChatGPT Pro
Yes
Cohere
Yes
Coral
Yes
Docker
No
Pricing Details
Free
Open source
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
No
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
Vald
Website
vald.vdaas.org
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