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features
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support

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Description

Caffe is a deep learning framework designed with a focus on expressiveness, efficiency, and modularity, developed by Berkeley AI Research (BAIR) alongside numerous community contributors. The project was initiated by Yangqing Jia during his doctoral studies at UC Berkeley and is available under the BSD 2-Clause license. For those interested, there is an engaging web image classification demo available for viewing! The framework’s expressive architecture promotes innovation and application development. Users can define models and optimizations through configuration files without the need for hard-coded elements. By simply toggling a flag, users can seamlessly switch between CPU and GPU, allowing for training on powerful GPU machines followed by deployment on standard clusters or mobile devices. The extensible nature of Caffe's codebase supports ongoing development and enhancement. In its inaugural year, Caffe was forked by more than 1,000 developers, who contributed numerous significant changes back to the project. Thanks to these community contributions, the framework remains at the forefront of state-of-the-art code and models. Caffe's speed makes it an ideal choice for both research experiments and industrial applications, with the capability to process upwards of 60 million images daily using a single NVIDIA K40 GPU, demonstrating its robustness and efficacy in handling large-scale tasks. This performance ensures that users can rely on Caffe for both experimentation and deployment in various scenarios.

Description

Berkeley DB encompasses a suite of embedded key-value database libraries that deliver scalable and high-performance data management functionalities for various applications. Its products utilize straightforward function-call APIs for accessing and managing data efficiently. With Berkeley DB, developers can create tailored data management solutions that bypass the typical complexities linked with custom projects. The library offers a range of reliable building-block technologies that can be adapted to meet diverse application requirements, whether for handheld devices or extensive data centers, catering to both local storage needs and global distribution, handling data volumes that range from kilobytes to petabytes. This versatility makes Berkeley DB a preferred choice for developers looking to implement efficient data solutions.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

AWS Elastic Fabric Adapter (EFA) Yes 
AWS Marketplace Yes 
Amazon Web Services (AWS) Yes 
BI Book No 
Checkmk No 
DashboardFox No 
Docker Yes 
Fabric for Deep Learning (FfDL) Yes 
JanusGraph No 
Ketch No 
Lambda Yes 
Netdata No 
OpenVINO Yes 
Polyaxon Yes 
Pop!_OS Yes 
Wyn Enterprise No 
Zebra by Mipsology Yes 
eMite No 

Integrations

AWS Elastic Fabric Adapter (EFA) No 
AWS Marketplace No 
Amazon Web Services (AWS) No 
BI Book Yes 
Checkmk Yes 
DashboardFox Yes 
Docker No 
Fabric for Deep Learning (FfDL) No 
JanusGraph Yes 
Ketch Yes 
Lambda No 
Netdata Yes 
OpenVINO No 
Polyaxon No 
Pop!_OS No 
Wyn Enterprise Yes 
Zebra by Mipsology No 
eMite Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version Yes 

Pricing Details

No price information available.
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 No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours Yes 
Live Rep (24/7) Yes 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person Yes 

Vendor Details

Company Name

BAIR

Country

United States

Website

caffe.berkeleyvision.org

Vendor Details

Company Name

Oracle

Founded

1977

Country

United States

Website

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

Product Features

Deep Learning

Convolutional Neural Networks No 
Document Classification Yes 
Image Segmentation No 
ML Algorithm Library No 
Model Training No 
Neural Network Modeling No 
Self-Learning No 
Visualization Yes 

Product Features

NoSQL Database

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

Alternatives

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