Hortonworks Data Platform Integrations

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.

Apache Hive™, a data warehouse software, facilitates the reading, writing and management of large datasets that are stored in distributed storage using SQL. Structure can be projected onto existing data. Hive provides a command line tool and a JDBC driver to allow users to connect to it. Apache Hive is an Apache Software Foundation open-source project. It was previously a subproject to Apache® Hadoop®, but it has now become a top-level project. We encourage you to read about the project and share your knowledge. To execute traditional SQL queries, you must use the MapReduce Java API. Hive provides the SQL abstraction needed to integrate SQL-like query (HiveQL), into the underlying Java. This is in addition to the Java API that implements queries.

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.

Our platform allows businesses to use data, including its application in advanced analysis, machine learning and AI, to do great things without worrying that customers, employees or intellectual property are at risk. The Protegrity Data Protection Platform does more than just protect data. It also classifies and discovers data, while protecting it. It is impossible to protect data you don't already know about. Our platform first categorizes data, allowing users the ability to classify the type of data that is most commonly in the public domain. Once those classifications are established, the platform uses machine learning algorithms to find that type of data. The platform uses classification and discovery to find the data that must be protected. The platform protects data behind many operational systems that are essential to business operations. It also provides privacy options such as tokenizing, encryption, and privacy methods.

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.

Progress DataDirect is passionate about empowering applications with enterprise data. We offer cloud and on-premises connectivity solutions for relational, NoSQL and Big Data data sources. We design solutions for thousands of companies and top vendors in analytics, data management, and BI. Our high-value connectors are designed to reduce development costs for a variety data sources. For greater security and peace of mind, you can get 24/7 support from experts around the world. For faster SQL access, connect with easy-to-use and time-saving drivers. Our mission is to keep up with the changing trends in data connectivity. If we don't have the connector you need, we will help you design it. Integrate connectivity into an application or service.

Data-driven decision making has led to a surge in business data and an increase in demand for its analysis. IT departments are now looking to move away from expensive Enterprise Data Warehouses (EDW), and towards more cost-effective Big Data platforms such as Hadoop or AWS. The Total Cost of Ownership (TCO), for these new platforms, is approximately 10 times lower. They are not suitable for interactive BI applications as they lack the same performance and user concurrency as legacy EDWs. Jethro was created precisely for this purpose. Customers use Jethro to perform interactive BI with Big Data. Jethro is a transparent middle-tier that does not require any changes to existing apps and data. It is self-driving and requires no maintenance. Jethro is compatible to BI tools such as Microstrategy, Qlik and Tableau and is data source agnostic. Jethro meets the needs of business users by allowing thousands of concurrent users to run complex queries across billions of records.

Apache Hadoop is a software library that allows distributed processing of large data sets across multiple computers. It uses simple programming models. It can scale from one server to thousands of machines and offer local computations and storage. Instead of relying on hardware to provide high-availability, it is designed to detect and manage failures at the application layer. This allows for highly-available services on top of a cluster computers that may be susceptible to failures.

100% compatible with Netezza Upgrade via a single command-line line. Available on premises, in the cloud, or hybrid. IBM®, Netezza®, Performance Server for IBM Cloud Pack® Data is an advanced data warehouse platform and analytics platform that is available on premises or on the cloud. This next generation of Netezza includes enhancements to the in-database analytics capabilities. You can do data science and machinelearning with data volumes scaling to the petabytes. Fast failure recovery and failure detection. Upgrade existing systems with a single command-line command. Ability to query multiple systems simultaneously. Select the nearest availability zone or data center, select the required number of compute units, and then go. IBM®, Netezza®, Performance Server for IBM Cloud® for Data is available via Amazon Web Services, Microsoft Azure, and IBM Cloud®. Netezza can be deployed on a private cloud using IBM Cloud Pak Data System.

Power analytics allows you to track user behavior. Segment users based upon their behavior. With powerful AI, you can create engagement strategies. Certain handset manufacturers have placed restrictions on push notification delivery due to OS/Device limitations. Our product allows you to bypass these restrictions and reach an additional 20% of users. Our product ensures greater inbox reach. We have email consultants and industry experts who can help you with best practices. Avoid sending spam messages, which can damage your brand reputation and domain. You can easily localize your communication based upon language. Our platform supports multilingual architecture so you can reach your customers in their local language. Target users with uninstall data, acquisition source, and more. Segment users exactly the way you want. Start conversations, reduce churn, and gain powerful insights.

Track, assign, track, and execute tasks. Get powerful insight into your productivity. Automate more than 100 tasks and amplify human interactions using bots, group chat, and other tools. Get actionable insights to help line managers, HR professionals and CXO achieve more. Define your organizational structure, assign roles and permissions, and grant access rights. Manage the employee life cycle, from onboarding to termination, and publish letters. You can run error-free payroll, manage loans and reimbursements, and meet all statutory norms. Real-time attendance is used to manage attendance, holidays, shifts, and integration. 360-degree feedback can help you achieve your organizational goals and improve performance. Boost employee morale & improve employee engagement using engagement tools. Real-time attendance is used to manage shifts, holidays, integration, and attendance. 360-degree feedback can help you achieve your organizational goals and improve performance. Boost employee morale & improve employee engagement using engagement tools.

Doolytic is a leader in big data discovery, the convergence data discovery, advanced analytics and big data. Doolytic is bringing together BI experts to revolutionize self-service exploration of large data. This will unleash the data scientist in everyone. doolytic is an enterprise solution for native big data discovery. doolytic is built on open-source, scalable technologies that are best-of-breed. Lightening performance on billions and petabytes. Structured, unstructured, and real-time data from all sources. Advanced query capabilities for experts, Integration with R to enable advanced and predictive applications. With Elastic's flexibility, you can search, analyze, and visualize data in real-time from any format or source. You can harness the power of Hadoop data lakes without any latency or concurrency issues. doolytic solves common BI issues and enables big data discovery without clumsy or inefficient workarounds.

Amadea technology uses the fastest real-time modeling and calculation engine on the market. You can create, deploy, and automate your analytics projects in one integrated environment. Data quality is key to successful analytical projects. Amadea, the fastest real-time calculation engine on the market, allows companies to prepare large and/or complex data and to use it in real time, regardless of its volume. ISoft was founded on the simple observation that successful analytical projects require participation of business users at all stages. Amadea is accessible to all users and was built on a simple interface that is easy to use. Amadea's fastest real-time calculation engine allows you to specify, prototype, and build your data applications simultaneously. Amadea has the fastest real-time data analytics engine on the market with 10 million lines per second and per core for standard calculations.

R Systems' goal is to help organizations identify and mitigate customer journey hindrances. This is done by using the power of AI, data analysis, natural language processing (NLP), and deep neural networks (DNN). Understanding the essence of customer experience will help you improve the way customers respond to your brand in terms engagement, loyalty, retention. To gain actionable insights and make informed decisions about retaining and acquiring customers, organizations need accurate data and metrics. Our data analytics framework will allow you to improve First Contact Resolution (FCR), reduce customer effort and optimize self-service options. It can also help you manage seasonal spikes in demand. Your customer experience will improve with every interaction when R Systems is on your side. Our services allow you to collect data from customer interactions to gain insight into behavior.

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.