Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Oracle AI Vector Search is an innovative feature integrated into Oracle Database, specifically tailored for AI applications, which enables the querying of data based on its semantic meaning rather than relying solely on conventional keyword searches. This functionality empowers organizations to conduct similarity searches across both structured and unstructured datasets, allowing for retrieval of results that prioritize contextual relevance over precise matches. Employing vector embeddings to represent various forms of data—including text, images, and documents—it utilizes advanced vector indexing and distance metrics to quickly locate similar items. Moreover, it introduces a unique VECTOR data type along with SQL operators and syntax that enable developers to merge semantic searches with relational queries within a single database framework. As a result, this integration streamlines the data management process by negating the necessity for separate vector databases, ultimately minimizing data fragmentation and fostering a cohesive environment for both AI and operational data. The enhanced capability not only simplifies the architecture but also enhances the overall efficiency of data retrieval and analysis in complex AI workloads.
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.
API Access
Has API
Yes
API Access
Has API
No
Integrations
Docker
No
Go
No
IBM watsonx.data
No
JSON
Yes
Java
No
Kubernetes
No
My DSO Manager
Yes
Node.js
No
Oracle Database
Yes
Python
No
Integrations
Docker
Yes
Go
Yes
IBM watsonx.data
Yes
JSON
No
Java
Yes
Kubernetes
Yes
My DSO Manager
No
Node.js
Yes
Oracle Database
No
Python
Yes
Pricing Details
No price information available.
Free Trial
Yes
Free Version
No
Pricing Details
Free
Open source
Free Trial
No
Free Version
Yes
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
Yes
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Oracle
Country
United States
Website
www.oracle.com/database/ai-vector-search/
Vendor Details
Company Name
Vald
Website
vald.vdaas.org