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Azore CFDAzore is a software tool designed for computational fluid dynamics (CFD) that focuses on the analysis of fluid movement and thermal transfers. By utilizing CFD, engineers and scientists can numerically tackle a diverse array of problems related to fluid mechanics, thermal dynamics, and chemical interactions through computer simulations. Azore excels in modeling a variety of fluid dynamics scenarios, encompassing air, liquids, gases, and flows containing particles. Its applications are vast, including the modeling of liquid flow through piping systems and assessing water velocity profiles around submerged objects. Furthermore, Azore is adept at simulating the behavior of gases and air, allowing for the exploration of ambient air velocity patterns as they navigate around structures, as well as examining flow dynamics, heat transfer, and mechanical systems within enclosed spaces. This robust CFD software can effectively model nearly any incompressible fluid flow scenario, addressing challenges associated with conjugate heat transfer, species transport, and both steady-state and transient flow conditions. With such capabilities, Azore serves as an invaluable asset for professionals in various engineering and scientific fields requiring precise fluid dynamics simulations.
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GreenhouseGreenhouse is more than an ATS – they’re a true hiring partner that gives companies of all sizes everything they’ll ever need to get measurably better at hiring. With Greenhouse, organizations can cut recruiting costs and ensure every hire is the right hire. Their industry-leading, AI-powered software supports every stage of the hiring process, from sourcing to onboarding, empowering companies to hire top talent quickly, consistently and fairly – today and as their business grows. With a structured hiring approach at its core, Greenhouse makes it easy to define the role, requirements and attributes of a successful candidate before a job is posted, enabling internal alignment and more confident, data-driven decisions. They’ve helped over 7,500 companies across diverse industry verticals and scaling goals turn talent into a strategic advantage, so they can be ready to hire for what’s next. Some of the most successful companies, like Hubspot, Block, NFL, Lyft, Trivago and HelloFresh, use Greenhouse for data and guidance on the behaviors and capabilities they need to improve their overall hiring performance. They have also received numerous awards showcasing their commitment to product innovation and great hiring, including: G2 Top 50 Best HR Products (2025), G2 Best Enterprise Products (2025), Fortune Best Workplaces (2019–2024) and Inc. 5000 (2018–2024). © 2024, Greenhouse Software, Inc. All rights reserved. "Hire for what's next," “The/Your all-together hiring platform,” "Talent Makers" and the G Logo are trademarks of Greenhouse Software, Inc.
What is Apache TinkerPop?
Apache TinkerPop™ is a dynamic graph computing framework that caters to both online transaction processing (OLTP) in graph databases and online analytical processing (OLAP) within graph analytic systems. At the heart of this framework lies Gremlin, a robust graph traversal language that empowers users to craft complex queries and traversals on their application's property graph with finesse. Each traversal in Gremlin comprises a sequence of steps that can be nested, offering significant flexibility in how data is explored and analyzed. Fundamentally, a graph is formed by interconnected vertices and edges, each capable of containing various key/value pairs referred to as properties. Vertices represent unique entities such as people, places, or events, while edges denote the relationships that link these vertices together. For instance, a vertex could signify an individual who knows another person, attended a specific event, or visited a certain place recently. This framework proves especially advantageous when tackling intricate domains filled with diverse objects (vertices) that can be linked through various types of relationships (edges). By grasping this structural design, users can maximize the potential of their data and extract meaningful insights from their interconnected networks. Ultimately, the ability to navigate and analyze such complex relationships enhances decision-making processes and drives innovation across various fields.
What is Amazon Neptune?
Amazon Neptune is a powerful and efficient fully managed graph database service that supports the development and operation of applications reliant on complex interconnected datasets. At its foundation is a uniquely crafted, high-performance graph database engine optimized for storing extensive relational data while executing queries with minimal latency. Neptune supports established graph models like Property Graph and the W3C's RDF, along with their associated query languages, Apache TinkerPop Gremlin and SPARQL, which facilitates the effortless crafting of queries that navigate intricate datasets. This service plays a crucial role in numerous graph-based applications, such as recommendation systems, fraud detection, knowledge representation, drug research, and cybersecurity initiatives. Additionally, it equips users with tools to actively identify and analyze IT infrastructure through an extensive security framework. Furthermore, the service provides visualization capabilities for all infrastructure components, which assists in planning, forecasting, and mitigating risks effectively. By leveraging Neptune, organizations can generate graph queries that swiftly identify identity fraud patterns in near-real-time, especially concerning financial transactions and purchases, thereby significantly enhancing their overall security protocols. Ultimately, the adaptability and efficiency of Neptune make it an invaluable resource for businesses seeking to harness the power of graph databases.
Integrations Supported
G.V() - Gremlin IDE
AWS App Mesh
AWS Marketplace
Amazon Quantum Ledger Database (QLDB)
Apache Groovy
Docker
Java
KeyLines
KgBase
New Relic
Integrations Supported
G.V() - Gremlin IDE
AWS App Mesh
AWS Marketplace
Amazon Quantum Ledger Database (QLDB)
Apache Groovy
Docker
Java
KeyLines
KgBase
New Relic
API Availability
Has API
API Availability
Has API
Pricing Information
Free
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
Apache Software Foundation
Company Location
United States
Company Website
tinkerpop.apache.org
Company Facts
Organization Name
Amazon
Date Founded
1994
Company Location
United States
Company Website
aws.amazon.com/neptune/
Categories and Features
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