EmbeddinghubFeatureform
|
Oracle AI Vector SearchOracle
|
|||||
Related Products
|
||||||
About
Operationalize your embeddings with one simple tool. Experience a comprehensive database designed to provide embedding functionality that, until now, required multiple platforms. Elevate your machine learning quickly and painlessly through Embeddinghub.
Embeddings are dense, numerical representations of real-world objects and relationships, expressed as vectors. They are often created by first defining a supervised machine learning problem, known as a "surrogate problem." Embeddings intend to capture the semantics of the inputs they were derived from, subsequently getting shared and reused for improved learning across machine learning models. Embeddinghub lets you achieve this in a streamlined, intuitive way.
|
About
Oracle AI Vector Search is a capability within Oracle Database designed for AI workloads that enables querying data based on semantics or meaning rather than traditional keyword matching. It allows organizations to search both structured and unstructured data using similarity search, making it possible to retrieve results based on contextual relevance instead of exact values. It uses vector embeddings to represent data such as text, images, or documents, and applies specialized vector indexes and distance functions to efficiently identify similar items. It introduces a native VECTOR data type, along with SQL operators and syntax that allow developers to combine semantic search with relational queries on business data in a single database environment. This eliminates the need for separate vector databases and reduces data fragmentation by keeping AI and operational data unified.
|
|||||
Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
|
Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
|
|||||
Audience
Machine learning developers interested in a powerful vector/embeddings database
|
Audience
Enterprises and developers who need to build AI applications that perform semantic search and generate context-aware results directly on business data
|
|||||
Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Not Supported
|
Support
Phone Support
Supported
24/7 Live Support
Not Supported
Online
Supported
|
|||||
API
Offers API
Not Supported
|
API
Offers API
Supported
|
|||||
Screenshots and Videos |
Screenshots and Videos |
|||||
Pricing
Free
Free Version
Supported
Free Trial
Not Supported
|
Pricing
No information available.
Free Version
Not Supported
Free Trial
Supported
|
|||||
Reviews/
|
Reviews/
|
|||||
Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
|
Training
Documentation
Supported
Webinars
Not Supported
Live Online
Supported
In Person
Not Supported
|
|||||
Company InformationFeatureform
Founded: 2019
United States
www.featureform.com/embeddinghub
|
Company InformationOracle
United States
www.oracle.com/database/ai-vector-search/
|
|||||
Alternatives |
Alternatives |
|||||
|
|
||||||
|
|
||||||
|
|
|
|||||
Categories |
Categories |
|||||
Integrations
JSON
Not Supported
My DSO Manager
Not Supported
Oracle Database
Not Supported
SQL
Not Supported
|
Integrations
JSON
Supported
My DSO Manager
Supported
Oracle Database
Supported
SQL
Supported
|
|||||
|
|
|