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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
Weaviate serves as an open-source vector database that empowers users to effectively store data objects and vector embeddings derived from preferred ML models, effortlessly scaling to accommodate billions of such objects. Users can either import their own vectors or utilize the available vectorization modules, enabling them to index vast amounts of data for efficient searching. By integrating various search methods, including both keyword-based and vector-based approaches, Weaviate offers cutting-edge search experiences. Enhancing search outcomes can be achieved by integrating LLM models like GPT-3, which contribute to the development of next-generation search functionalities. Beyond its search capabilities, Weaviate's advanced vector database supports a diverse array of innovative applications. Users can conduct rapid pure vector similarity searches over both raw vectors and data objects, even when applying filters. The flexibility to merge keyword-based search with vector techniques ensures top-tier results while leveraging any generative model in conjunction with their data allows users to perform complex tasks, such as conducting Q&A sessions over the dataset, further expanding the potential of the platform. In essence, Weaviate not only enhances search capabilities but also inspires creativity in app development.
API Access
Has API
API Access
Has API
Integrations
Assembly
ChatGPT Plus
ChatGPT Pro
Coral
GPT-3
GlassFlow
Google Cloud Platform
Haystack
IBM watsonx.data
JSON
Integrations
Assembly
ChatGPT Plus
ChatGPT Pro
Coral
GPT-3
GlassFlow
Google Cloud Platform
Haystack
IBM watsonx.data
JSON
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
Free
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
Oracle
Country
United States
Website
www.oracle.com/database/ai-vector-search/
Vendor Details
Company Name
Weaviate
Founded
2019
Country
The Netherlands
Website
weaviate.io