Table of Contents


  1. Preface
  2. Introduction to Informatica Edge Data Streaming
  3. Licenses
  4. Using Informatica Administrator
  5. Creating and Managing the Edge Data Streaming Service
  6. Edge Data Streaming Entity Types
  7. Edge Data Streaming Nodes
  8. Data Connections
  9. Working With Data Flows
  10. Managing the Edge Data Streaming Components
  11. Security
  12. High Availability
  13. Disaster Recovery
  14. Monitoring Edge Data Streaming Entities
  15. Appendix A: Troubleshooting
  16. Appendix B: Frequently Asked Questions
  17. Appendix C: Regular Expressions
  18. Appendix D: Command Line Program
  19. Appendix E: Configuring Edge Data Streaming to Work With a ZooKeeper Observer
  20. Appendix F: Glossary

User Guide

User Guide

Informatica Edge Data Streaming Overview

Informatica Edge Data Streaming

Informatica Edge Data Streaming (EDS) is a highly available, distributed, scalable, real-time application that collects and aggregates machine data. You can collect machine data from different types of sources, transform or process the data, and write it to different types of targets.
consists of source services that collect data from sources and target services that write data to targets.
You can use EDS to collect data from different types of sources, such as event logs, real-time logs, call detail records, TCP/UDP applications, Syslog sources, HTTP sources, WebSocket sources, and MQTT brokers.
You can stream data to different types of targets, such as a Hadoop Distributed File System (HDFS) cluster and Apache Cassandra. You can stream data to an Informatica PowerExchange® for Ultra Messaging source to perform complex transformations and real-time data warehousing. You can also stream data to Informatica RulePoint source controller to process complex events in real time.
To gather operational intelligence from machine data or to perform real-time data warehousing, you need to collect and analyze the data before it becomes obsolete or corrupted. Use
to aggregate data from multiple sources in real time. If the data is in a form that is difficult to analyze, you can configure filters and transformations in
to prepare the data for analysis.
You can configure
for high availability so the processing fails over to a backup component when a primary component is unavailable. You can also use EDS to securely transfer data from sources to targets.


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