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Average Ratings 0 Ratings
Description
Gemini Embedding models, which include the advanced Gemini Embedding 2, are integral to Google's Gemini AI framework and are specifically created to translate text, phrases, sentences, and code into numerical vector forms that encapsulate their semantic significance. In contrast to generative models that create new content, these embedding models convert input into dense vectors that mathematically represent meaning, facilitating the comparison and analysis of information based on conceptual relationships instead of precise wording. This functionality allows for various applications, including semantic search, recommendation systems, document retrieval, clustering, classification, and retrieval-augmented generation processes. Additionally, the model accommodates input in over 100 languages and can handle requests of up to 2048 tokens, enabling it to effectively embed longer texts or code while preserving a deep contextual understanding. Ultimately, the versatility and capability of the Gemini Embedding models play a crucial role in enhancing the efficacy of AI-driven tasks across diverse fields.
Description
ParadeDB enhances Postgres tables by introducing column-oriented storage alongside vectorized query execution capabilities. At the time of table creation, users can opt for either row-oriented or column-oriented storage. The data in column-oriented tables is stored as Parquet files and is efficiently managed through Delta Lake. It features keyword search powered by BM25 scoring, adjustable tokenizers, and support for multiple languages. Additionally, it allows semantic searches that utilize both sparse and dense vectors, enabling users to achieve improved result accuracy by merging full-text and similarity search techniques. Furthermore, ParadeDB adheres to ACID principles, ensuring robust concurrency controls for all transactions. It also seamlessly integrates with the broader Postgres ecosystem, including various clients, extensions, and libraries, making it a versatile option for developers. Overall, ParadeDB provides a powerful solution for those seeking optimized data handling and retrieval in Postgres.
API Access
Has API
API Access
Has API
Integrations
Amazon S3
Gemini
Gemini Enterprise
Gemini Enterprise Agent Platform
Google AI Studio
Microsoft Azure
PostgreSQL
Python
Integrations
Amazon S3
Gemini
Gemini Enterprise
Gemini Enterprise Agent Platform
Google AI Studio
Microsoft Azure
PostgreSQL
Python
Pricing Details
Free
Free Trial
Free Version
Pricing Details
No price information available.
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
Founded
1998
Country
United States
Website
blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-embedding-2/
Vendor Details
Company Name
ParadeDB
Website
www.paradedb.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