Best IT Management Software for Hortonworks Data Platform

Open source platform for machine learning. TensorFlow is a machine learning platform that is open-source and available to all. It offers a flexible, comprehensive ecosystem of tools, libraries, and community resources that allows researchers to push the boundaries of machine learning. Developers can easily create and deploy ML-powered applications using its tools. Easy ML model training and development using high-level APIs such as Keras. This allows for quick model iteration and debugging. No matter what language you choose, you can easily train and deploy models in cloud, browser, on-prem, or on-device. It is a simple and flexible architecture that allows you to quickly take new ideas from concept to code to state-of the-art models and publication. TensorFlow makes it easy to build, deploy, and test.

Amazon Simple Storage Service (Amazon S3), an object storage service, offers industry-leading scalability and data availability, security, performance, and scalability. Customers of all sizes and industries can use Amazon S3 to store and protect any amount data for a variety of purposes, including data lakes, websites and mobile applications, backup, restore, archive, enterprise apps, big data analytics, and IoT devices. Amazon S3 offers easy-to-use management tools that allow you to organize your data and set up access controls that are tailored to your business, organizational, or compliance needs. Amazon S3 is built for 99.999999999% (11 9,'s) of durability and stores data for millions applications for companies around the globe. You can scale your storage resources to meet changing demands without having to invest upfront or go through resource procurement cycles. Amazon S3 is designed to last 99.999999999% (11 9,'s) of data endurance.

All sizes of companies can use object storage. You can store any amount of data. You can retrieve it as often and as often as you like. You can configure your data with Object Lifecycle Management to automatically transition to lower cost storage classes when it meets certain criteria, such as when it reaches a certain date or when you have stored a newer version. Cloud Storage offers a growing number of storage locations that you can store your data, with multiple redundancy options. You can choose where and how to store your data, regardless of whether you want to optimize for a split-second response or create a robust disaster recovery strategy. Two highly efficient online routes to Cloud Storage are Storage Transfer Service and Transfer Service. Both offer the speed and scalability you need to make data transfers faster. Our Transfer Appliance is a shippable storage device that can be used for offline data transfer.

Docker eliminates repetitive, tedious configuration tasks and is used throughout development lifecycle for easy, portable, desktop, and cloud application development. Docker's complete end-to-end platform, which includes UIs CLIs, APIs, and security, is designed to work together throughout the entire application delivery cycle. Docker images can be used to quickly create your own applications on Windows or Mac. Create your multi-container application using Docker Compose. Docker can be integrated with your favorite tools in your development pipeline. Docker is compatible with all development tools, including GitHub, CircleCI, and VS Code. To run applications in any environment, package them as portable containers images. Use Docker Trusted Content to get Docker Official Images, images from Docker Verified Publishings, and more.

We make BI and Big Data analytics easier and more efficient. Our goal is to empower business users, make BI specialists and always-busy business more independent when solving data-driven business problems. Querona is a solution for those who have ever been frustrated by a lack in data, slow or tedious report generation, or a long queue to their BI specialist. Querona has a built-in Big Data engine that can handle increasing data volumes. Repeatable queries can be stored and calculated in advance. Querona automatically suggests improvements to queries, making optimization easier. Querona empowers data scientists and business analysts by giving them self-service. They can quickly create and prototype data models, add data sources, optimize queries, and dig into raw data. It is possible to use less IT. Users can now access live data regardless of where it is stored. Querona can cache data if databases are too busy to query live.

The fundamental idea of YARN is to split up the functionalities of resource management and job scheduling/monitoring into separate daemons. The idea is to have a global ResourceManager, (RM), and a per-application ApplicationMaster, (AM). An application can be a single job, or a DAG (distributed array of jobs). The data-computation framework is formed by the NodeManager and the ResourceManager. The ResourceManager is the ultimate authority who arbitrates the allocation of resources among all applications in the system. The NodeManager is the per-machine framework agent who is responsible for containers, monitoring their resource usage (cpu, memory, disk, network) and reporting the same to the ResourceManager/Scheduler. The per-application ApplicationMaster, which is in essence a framework-specific library, is responsible for negotiating resources from ResourceManager and working with NodeManagers to execute and monitor tasks.