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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

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

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

IBM watsonx.data
Java
Amazon Web Services (AWS)
Azure Marketplace
ChatGPT
ChatGPT Plus
ChatGPT Pro
Cohere
Coral
Docker
Go
Google Cloud Platform
HoneyHive
Hugging Face
Kubernetes
Milvus
Node.js
OpenAI
PyTorch
Python

Integrations

IBM watsonx.data
Java
Amazon Web Services (AWS)
Azure Marketplace
ChatGPT
ChatGPT Plus
ChatGPT Pro
Cohere
Coral
Docker
Go
Google Cloud Platform
HoneyHive
Hugging Face
Kubernetes
Milvus
Node.js
OpenAI
PyTorch
Python

Pricing Details

Free
Free Trial
Free Version

Pricing Details

$0
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

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

Alternatives

Embeddinghub Reviews

Embeddinghub

Featureform

Alternatives

Embeddinghub Reviews

Embeddinghub

Featureform
Milvus Reviews

Milvus

Zilliz