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What is Solver SDK?

Easily integrate optimization and simulation models into your desktop, web, or mobile applications by leveraging consistent high-level objects such as Problem, Solver, Variable, and Function, along with their collections, properties, and methods that span multiple programming languages. This consistency is enhanced by a standardized object-oriented API that clients can access remotely through Web Services WS-* standards, catering to languages like PHP, JavaScript, and C#. Moreover, procedural languages can conveniently execute traditional calls that align well with the object-oriented API's properties and methods. The array of optimization techniques offered includes linear and quadratic programming, mixed-integer programming, smooth nonlinear optimization, as well as global optimization and non-smooth evolutionary and tabu search techniques. In addition, you can seamlessly incorporate top-notch optimization tools from Gurobiâ„¢, XPRESSâ„¢, and MOSEKâ„¢ for linear, quadratic, and conic models, as well as KNITROâ„¢, SQP, and GRG methods for addressing nonlinear challenges, all within the Solver SDK framework. The ability to generate a sparse DoubleMatrix object with an impressive scale of 1 million rows and columns simplifies the management of extensive datasets. This adaptability in creating and optimizing complex problems empowers developers to craft solutions that are not only efficient but also finely tuned to the unique requirements of their applications, thereby enhancing overall productivity.

What is DataMelt?

DataMelt, commonly referred to as "DMelt," is a versatile environment designed for numerical computations, data analysis, data mining, and computational statistics. It facilitates the plotting of functions and datasets in both 2D and 3D, enables statistical testing, and supports various forms of data analysis, numeric computations, and function minimization. Additionally, it is capable of solving linear and differential equations, and provides methods for symbolic, linear, and non-linear regression. The Java API included in DataMelt integrates neural network capabilities alongside various data manipulation techniques utilizing different algorithms. Furthermore, it offers support for symbolic computations through Octave/Matlab programming elements. As a computational environment based on a Java platform, DataMelt is compatible with multiple operating systems and supports various programming languages, distinguishing it from other statistical tools that often restrict users to a single language. This software uniquely combines Java, the most prevalent enterprise language globally, with popular data science scripting languages such as Jython (Python), Groovy, and JRuby, thereby enhancing its versatility and user accessibility. Consequently, DataMelt emerges as an essential tool for researchers and analysts seeking a comprehensive solution for complex data-driven tasks.

Media

Media

Integrations Supported

Integrations Supported

Apache NetBeans
Eclipse BIRT

API Availability

API Availability

Has API

Pricing Information

$2495 one-time payment

Pricing Information

$0
Access to full documentation (examples, Java API documentation, online manual) requires one-time membership payment (20$/user)
Free Version

Supported Platforms

SaaS
Windows

Supported Platforms

Android
Windows
Mac
Linux

Customer Service / Support

Web-Based Support

Customer Service / Support

Standard Support

Training Options

Documentation Hub
Online Training

Training Options

Documentation Hub
On-Site Training

Company Facts

Organization Name

Frontline Systems

Company Website

www.solver.com/solver-sdk-platform

Company Facts

Organization Name

jWork.ORG

Date Founded

2005

Company Location

United States

Company Website

datamelt.org

Categories and Features

IT Risk Management

Not specified

Risk Management

Not specified

Simulation

3D Modeling
Agent-Based Modeling
Industry Specific Database
Monte Carlo Simulation
Presentation Tools
Stochastic Modeling
Turbulence Modeling

Categories and Features

Artificial Intelligence

For Healthcare
Image Recognition
Machine Learning
Natural Language Processing
Predictive Analytics

Data Analysis

Data Discovery
Data Visualization
Predictive Analytics
Regression Analysis
Statistical Modeling
Text Analytics

Data Mining

Data Extraction
Data Visualization
Machine Learning
Predictive Modeling
Statistical Analysis
Text Mining

Data Visualization

Analytics
Simulation Models
Visual Discovery

Deep Learning

Convolutional Neural Networks
Document Classification
ML Algorithm Library
Model Training
Self-Learning
Visualization

Education

Not specified

Neural Network

Not specified

Statistical Analysis

Analytics
Association Discovery
Compliance Tracking
File Management
File Storage
Forecasting
Multivariate Analysis
Regression Analysis
Statistical Simulation
Survival Analysis
Time Series
Visualization

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