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Maximize the Value of Data-in-Motion with Big Data from the Internet of Things

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Hortonworks DataFlow (HDF™)

Hortonworks DataFlow (HDF)

Hortonworks DataFlow (HDF) provides the only end-to-end platform that collects, curates, analyzes and acts on data in real-time, on-premises or in the cloud, with a drag-and-drop visual interface. HDF is an integrated solution with Apache Nifi/MiNifi, Apache Kafka, Apache Storm and Druid.

The HDF streaming real-time data analytics platform includes Data Flow Management Systems, Stream Processing, and Enterprise Services.

Powering the Future of Data
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HDF Data-In-Motion Platform

Three Major Components of Hortonworks DataFlow

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Easy, Secure, and Reliable Way to Manage Data Flow 

Collect and manipulate internet of things big data flows securely and efficiently while giving real-time operational visibility, control, and management.

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Immediate and Continuous Insights  

Build streaming analytics applications in minutes to capture perishable insights in real-time without writing a single line of code.

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Corporate Governance, Security and Operations 

Manage the HDF and HDP ecosystem with comprehensive management panel for provisioning, monitoring, and governance.

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与数据源无关的集成式收集平台

HDF has full featured data collection capabilities that are streaming data agnostic and integrated with over 220 processors. Big Data from the internet of things can be collected from dynamic and distributed sources of differing formats, schemas, protocols, speeds and sizes and from types such as machines, geo location devices, click streams, files, social feeds, log files and videos.

更多信息:

  • How real-time data-source agnostic dataflow management makes data movement easy
    Watch Video
    Learn More
    Learn what HDF can do to optimize log analytics from the Edge.Read More
Powerful Data Collection

REAL-TIME RESPONSE TO DATA-IN-MOTION

With HDF, data collection is no longer a tedious process. You can manage data in full flight with a visual control panel to adjust sources, join and split streams, and prioritize data flow. HDF also can add contextual data to your streams for more complete analysis and insight. The always-on data provenance and audit trails provide security and governance compliance and troubleshooting as necessary in real-time. Integrated with Apache NiFi, MiNiFi, Kafka and Storm, HDF is ready for high volume event processing for immediate analysis and action. Kafka allows differing rates of data creation and delivery while Storm provides streaming real-time data analytics and immediate insights at a massive scale.

更多信息:

  • 流数据如何通过 Apache NiFi 实时可视用户界面提升运营效能。
    观看视频
Real-Time Data Flow Management

FULLY SECURE FROM SOURCE TO DESTINATION 

HDF secures end-to-end data flow and routing from source to destination with discrete user authorization and detailed, real-time visual chain of custody. Use the visual user interface of HDF to encrypt streaming data, route it to Kafka, configure buffers and manage congestion so that data can be dynamically prioritized and securely sent. HDF enables role-based data access that allows enterprises to dynamically and securely share select pieces of pertinent data. HDF can easily deploy flow management and streaming applications in a Kerberized environment without much operational overhead.

更多信息:

  • See how granular access of data is better than role based access
    Watch Video
Enterprise-Grade Security

BUILD STREAMING ANALYTICS APPLICATIONS WITHOUT CODE

HDF includes a complete streaming analytics module, Streaming Analytics Manager (SAM), to build streaming analytics applications that do event correlation, context enrichment, complex pattern matching, analytical aggregations and create alerts/notifications when insights are discovered. SAM makes building streaming analytics easy for application developers, DevOps and business analysts to build, develop, collaborate, analyze, deploy, and manage applications in minutes without writing a single line of code. Analysts use pre-built charts to quickly build analysis and create dashboards, while DevOps can manage and monitor the applications performance right out of the box.

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MORE EFFICIENT OPERATIONS WITH SCHEMA REGISTRY

HDF includes, Schema Registry, a central schema repository that allows analytics applications to flexibly interact with each other. This enables users to save, edit, or retrieve schemas for the data they need. This also allows easy attachment of schemas to each data without incurring additional overhead for greater operational efficiency. With schema version management, data consumers and data producers can evolve at different rates. And, through schema validation, data quality is greatly improved. A central schema registry also provides for greater governance of how data is used. Schema Registry is integrated with Apache Nifi and HDF Streaming Analytics Manager.

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WHAT’S NEW IN HDF

Build Real-Time Analytics Faster with Streaming Analytics Manager

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Build analytics applications easily with drag and drop visual paradigm with drop down analytics functions

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Analyze quickly with rich visual dashboard and an analytics engine powered by Druid

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Operate efficiently with prebuilt monitoring dashboards of system metrics

Manage Data Flows More Easily with Schema Registry

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Eliminate the need to code and attach schema to every piece of data and reduce operational overhead

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Allow data consumers and producers to evolve at different rates with schema version management

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Store schema for any type of entity or data store, not just Kafka

HDF 用户指南

获取 HDF 发行说明;用户版、开发者版指南并开始使用。

支持

业内针对企业内部 Apache NiFi、Kafka 和 Storm 提供支持的最佳团队。请联系我们的专家团队,由他们指引您开启这段旅程。

培训

大数据专家提供的实时培训。可当面提供,也可在您需要的任何时候按需提供。