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What is Oracle Berkeley DB?

Berkeley DB consists of a collection of embedded key-value database libraries designed to provide scalable and high-performance data management capabilities for a wide array of applications. The libraries feature simple function-call APIs that facilitate efficient data access and management. By leveraging Berkeley DB, developers can craft customized data management solutions that avoid the usual difficulties associated with bespoke projects. The library includes a variety of dependable building-block technologies that can be tailored to satisfy different application needs, whether for mobile devices or large-scale data centers, addressing both local storage requirements and global distribution challenges. This adaptability allows it to manage data volumes that span from kilobytes to petabytes. Consequently, Berkeley DB stands out as a favored option among developers seeking to implement effective data solutions, making it a versatile tool in the realm of data management. Its capability to cater to diverse environments further solidifies its reputation in the industry.

What is Caffe?

Caffe is a robust deep learning framework that emphasizes expressiveness, efficiency, and modularity, and it was developed by Berkeley AI Research (BAIR) along with several contributors from the community. Initiated by Yangqing Jia during his PhD studies at UC Berkeley, this project operates under the BSD 2-Clause license. An interactive web demo for image classification is also available for exploration by those interested! The framework's expressive design encourages innovation and practical application development. Users are able to create models and implement optimizations using configuration files, which eliminates the necessity for hard-coded elements. Moreover, with a simple toggle, users can switch effortlessly between CPU and GPU, facilitating training on powerful GPU machines and subsequent deployment on standard clusters or mobile devices. Caffe's codebase is highly extensible, which fosters continuous development and improvement. In its first year alone, over 1,000 developers forked Caffe, contributing numerous enhancements back to the original project. These community-driven contributions have helped keep Caffe at the cutting edge of advanced code and models. With its impressive speed, Caffe is particularly suited for both research endeavors and industrial applications, capable of processing more than 60 million images per day on a single NVIDIA K40 GPU. This extraordinary performance underscores Caffe's reliability and effectiveness in managing extensive tasks. Consequently, users can confidently depend on Caffe for both experimentation and deployment across a wide range of scenarios, ensuring that it meets diverse needs in the ever-evolving landscape of deep learning.

Media

Media

Integrations Supported

AWS Elastic Fabric Adapter (EFA)
AWS Marketplace
Amazon Web Services (AWS)
BI Book
Checkmk
DashboardFox
Docker
Fabric for Deep Learning (FfDL)
JanusGraph
Ketch
Lambda
NVIDIA DIGITS
Netdata
OpenVINO
Wyn Enterprise
Zebra by Mipsology
eMite

Integrations Supported

AWS Elastic Fabric Adapter (EFA)
AWS Marketplace
Amazon Web Services (AWS)
BI Book
Checkmk
DashboardFox
Docker
Fabric for Deep Learning (FfDL)
JanusGraph
Ketch
Lambda
NVIDIA DIGITS
Netdata
OpenVINO
Wyn Enterprise
Zebra by Mipsology
eMite

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Oracle

Date Founded

1977

Company Location

United States

Company Website

www.oracle.com/database/technologies/related/berkeleydb.html

Company Facts

Organization Name

BAIR

Company Location

United States

Company Website

caffe.berkeleyvision.org

Categories and Features

NoSQL Database

Auto-sharding
Automatic Database Replication
Data Model Flexibility
Deployment Flexibility
Dynamic Schemas
Integrated Caching
Multi-Model
Performance Management
Security Management

Categories and Features

Deep Learning

Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization

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