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RaimaDBRaimaDB is an embedded time series database designed specifically for Edge and IoT devices, capable of operating entirely in-memory. This powerful and lightweight relational database management system (RDBMS) is not only secure but has also been validated by over 20,000 developers globally, with deployments exceeding 25 million instances. It excels in high-performance environments and is tailored for critical applications across various sectors, particularly in edge computing and IoT. Its efficient architecture makes it particularly suitable for systems with limited resources, offering both in-memory and persistent storage capabilities. RaimaDB supports versatile data modeling, accommodating traditional relational approaches alongside direct relationships via network model sets. The database guarantees data integrity with ACID-compliant transactions and employs a variety of advanced indexing techniques, including B+Tree, Hash Table, R-Tree, and AVL-Tree, to enhance data accessibility and reliability. Furthermore, it is designed to handle real-time processing demands, featuring multi-version concurrency control (MVCC) and snapshot isolation, which collectively position it as a dependable choice for applications where both speed and stability are essential. This combination of features makes RaimaDB an invaluable asset for developers looking to optimize performance in their applications.
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What is VectorCAST?
VectorCAST is a comprehensive test-automation framework designed to enhance unit, integration, and system testing throughout the embedded software development lifecycle. This tool streamlines the automation of both test case creation and execution for applications developed in C, C++, and Ada, while being adaptable to various environments including host, target, and continuous integration setups. Furthermore, VectorCAST offers critical structural code coverage metrics that are vital for validating safety-critical and mission-critical applications. It integrates effortlessly with simulation processes such as software-in-the-loop and processor-in-the-loop, and it collaborates effectively with model-based engineering tools like Simulink/Embedded Coder. In addition, the framework supports sophisticated white-box testing methodologies, such as dynamic instrumentation, fault injection, and test harness generation, by skillfully merging static analysis outcomes—like those provided by Polyspace—with dynamic coverage for thorough lifecycle verification. Significant functionalities include the ability to link requirements directly with tests and the comprehensive management and reporting of coverage across various configurations, which ultimately streamlines the testing process and improves efficiency. By leveraging VectorCAST, organizations can significantly enhance the reliability and effectiveness of their software testing practices, making it an invaluable asset in their development toolkit. This ultimately leads to a more robust software product that meets the highest quality standards.
What is AWS Fault Injection Service?
Recognize the limitations in performance and potential weaknesses that traditional software testing may overlook. It is crucial to set definitive guidelines for stopping an experiment or returning to the pre-experiment state. Conduct tests rapidly by utilizing predefined scenarios from the extensive library provided by the AWS Fault Injection Service (FIS). By simulating authentic failure conditions, teams can gain deeper understanding of how different resources may perform under strain. As part of the AWS Resilience Hub, FIS serves as a robust tool for executing fault injection tests to improve application performance, visibility, and durability. The service simplifies the process of setting up and conducting controlled fault injection tests across various AWS services, which helps teams cultivate confidence in how their applications behave. Additionally, FIS incorporates vital safety features that allow teams to run experiments in production environments with safeguards in place, such as the automatic ability to halt or revert the experiment based on specific pre-established criteria, thereby enhancing overall safety during testing. This functionality equips development teams with the knowledge they need to navigate their applications in high-pressure situations and prepares them for unforeseen challenges. Ultimately, the use of FIS not only improves resilience but also fosters a more proactive approach to application performance management.
Integrations Supported
AWS Resilience Hub
Ada
Amazon Web Services (AWS)
Ansys SCADE Architect
Bamboo
C
C++
Codebeamer
Creo
IBM DOORS Next
Integrations Supported
AWS Resilience Hub
Ada
Amazon Web Services (AWS)
Ansys SCADE Architect
Bamboo
C
C++
Codebeamer
Creo
IBM DOORS Next
API Availability
Has API
API Availability
Has API
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Pricing Information
$0.10 per action-minute
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
VECTOR Informatik
Date Founded
1998
Company Location
Germany
Company Website
www.vector.com/us/en/products/products-a-z/software/vectorcast/
Company Facts
Organization Name
Amazon
Company Location
United States
Company Website
aws.amazon.com/fis/
Categories and Features
Software Testing
Automated Testing
Black-Box Testing
Dynamic Testing
Issue Tracking
Manual Testing
Quality Assurance Planning
Reporting / Analytics
Static Testing
Test Case Management
Variable Testing Methods
White-Box Testing