About Release 8.0.0
This site contains documentation for HPE Data Fabric release 8.0.0, including installation, configuration, administration, and reference content, as well as content for the associated ecosystem components and drivers.
8.0.0 Installation
This section contains information about installing HPE Data Fabric software. It also contains information about how to migrate data and applications from an Apache Hadoop cluster to a HPE Ezmeral Data Fabric cluster.
8.0.0 Upgrade
This section describes how to upgrade HPE Data Fabric software.
8.0.0 Data Fabric
HPE Data Fabric is the industry-leading data platform for AI and analytics that solves enterprise business needs.
8.0.0 Administration
This section describes how to manage the nodes and services that make up a cluster.
8.0.0 Development
This section contains information related to application development for Ezmeral ecosystem components and HPE Data Fabric products, including the file system, Database (Key-Value and JSON), and Event Streams.
- Application Development Process
  Before you start developing applications on the HPE Data Fabric platform, consider how you will get the data into the platform, the storage format of the data, the type of processing or modeling that is required, and how the data will be accessed.
- File Store and Apps
  The following sections provide information about accessing the File Store with C and Java applications.
- HPE Data Fabric Database and Apps
  This section contains information about developing client applications for JSON and key-value tables.
- Apache Kafka Wire Protocol Service
  HPE Data Fabric Streams supports Apache Kafka Wire Protocol Service. Apache Kafka Wire Protocol Service is a TCP/IP service that emulates a Kafka cluster backed by HPE Data Fabric Streams. The service makes it possible for Apache Kafka clients written in any programming language to access topics in HPE Data Fabric Streams.
- Model Context Protocol (MCP)
- HPE Data Fabric Streams and Apps
  HPE Data Fabric Streams brings integrated publish and subscribe messaging to HPE Data Fabric.
  - Getting Started with HPE Data Fabric Streams
    If you have a basic understanding of HPE Data Fabric Streams components and the typical flow of messages from producers to consumers, you can get started.
  - Consuming CDC Records
    The OJAI changelog interfaces are used to consume changed data records (propagated by the Change Data Capture feature).
  - Consuming Audit Logs
    Audit Streaming (available from v6.0.1) provides a way to process the audit data in real-time.
  - HPE Data Fabric Streams Java Applications
    This section contains information about developing client applications with Java, including information about the HPE Data Fabric Streams and Apache Kafka Java APIs, configuration parameters, and compiling and running producers and consumers.
  - HPE Data Fabric Streams C Applications
    You can develop C applications for HPE Data Fabric Streams. The HPE Data Fabric Streams C Client is a distribution of librdkafka that works with HPE Data Fabric Streams. The HPE Data Fabric Streams C Client is available in Ecosystem Pack (EEP) 3.0 and later.
  - HPE Data Fabric Streams Python Applications
    As of HPE Data Fabric 5.2.1, you can create python applications for HPE Data Fabric Streams using the HPE Data Fabric Streams Python client. The HPE Data Fabric Streams Python client is a binding for librdkafka and the HPE Data Fabric Streams C Client is a distribution of librdkafka that works with HPE Data Fabric Streams.
  - HPE Data Fabric Streams C#/.NET Applications
    As of HPE Data Fabric 6.0.1/EEP5.0, you can create C#/.NET applications for HPE Data Fabric Streams using the HPE Data Fabric Streams C#/.NET client. The HPE Data Fabric Streams C#/.NET client is a binding for librdkafka and the HPE Data Fabric Streams C Client is a distribution of librdkafka that works with HPE Data Fabric Streams.
    - Developing HPE Data Fabric Streams C#/.NET Applications
      Describes general tasks for developing C#/.NET applications.
    - Migrating Kafka C#/.NET Applications to HPE Data Fabric Streams
      With some modification, you can use existing confluent-kafka C#/.NET applications to consume and produce topics in HPE Data Fabric Streams. The HPE Data Fabric Streams C#/.NET Client is a binding for Apache librdkafka that works with HPE Data Fabric Streams.
    - API for HPE Data Fabric Streams C#/.NET
      HPE Data Fabric Streams C#/.NET Client is a binding for librdkafka and the HPE Data Fabric Streams C Client is a distribution of librdkafka that works with HPE Data Fabric Streams.
    - Configuration Properties for HPE Data Fabric Streams C#/.NET Client
      Describes the C#/.NET client configuration properties.
  - Utilities for HPE Data Fabric Streams
    HPE Data Fabric Streams provides the utilities for operating on streams and topics.
  - Configuring Properties for Message Size
    Describes the message.max.bytes and receive.message.max.bytes properties for configuring message size.
  - Synchronous Consumer Partition Assignment for Streams
    Describes synchronous consumer partition assigment for various applications that use Data Fabric Streams.
- MapReduce and Apps
  This section contains information associated with developing YARN applications.
- Kubernetes Interfaces for Data Fabric
  This section describes how to leverage the capabilities of the Kubernetes Interfaces for Data Fabric.
- Ecosystem Components
  The following sections provide information about each open-source project that is supported by the HPE Data Fabric.
- Maven and the HPE Data Fabric
  This section discusses topics associated with Maven and the HPE Data Fabric.
- Developer's Reference
  This section contains in-depth information for the developer.
- API Documentation
  HPE Data Fabric supports public APIs for file system, HPE Data Fabric Database, and HPE Data Fabric Streams. These APIs are available for application-development purposes.
Other Docs
This section contains release-independent information, including: Installer documentation, Ecosystem release notes, interoperability matrices, security vulnerabilities, and links to other Data Fabric version documentation.
Glossary
Definitions for commonly used terms in MapR Converged Data Platform environments.

HPE Data Fabric Streams C#/.NET Applications

As of HPE Data Fabric 6.0.1/EEP5.0, you can create C#/.NET applications for HPE Data Fabric Streams using the HPE Data Fabric Streams C#/.NET client. The HPE Data Fabric Streams C#/.NET client is a binding for librdkafka and the HPE Data Fabric Streams C Client is a distribution of librdkafka that works with HPE Data Fabric Streams.

Requirements

HPE Data Fabric Client on Windows 7 (or higher) x64 operating systems
HPE Data Fabric cluster version 6.0.1 or greater
Java 8 SDK and set Java HOME
HPE Data Fabric Streams C Client (mapr-librdkafka 0.11.3)
HPE Data Fabric Streams C#/.NET Client (mapr-streams-dotnet)
.NET SDK 4.5.x or 4.6.x or .NET Core SDK 1.1
nuget.exe

See Installing HPE Data Fabric Streams C#/.NET Client for installation information.

General Information

When developing and running HPE Data Fabric Streams C#/.NET applications, note the following points:

You can create producers and high-level consumers. Low-level consumers are not supported.
Consuming or producing topics in a Kafka cluster is not supported.
HPE Data Fabric Streams offset values start at 1, not 0.
HPE Data Fabric security is supported including ACLs and ACEs for authorization. The unique Kafka security features that are part of Apache Kafka are not supported. See Security for more information about HPE Data Fabric security features.
User impersonation is not supported.

Synchronous Consumer Partition Assignment

See Synchronous Consumer Partition Assignment for Streams

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HPE Data Fabric 8.0.0 Software Documentation
Abstract	This site contains documentation for HPE Data Fabric Software version 8.0.0 including installation, configuration, administration, and reference content, as well as content for the associated bundled ecosystem components and drivers.
Published	November 2025
Edition	8.0.0
Topic last updated	2025-02-05