DATA STREAM PROCESSING

Data stream processing is a crucial technology for organizations seeking to improve competitiveness by gleaning insight from real-time data streams.

What is data streaming? Data streaming refers to real-time, unbounded processing of data generated from hundreds or thousands of data sources such as mobile and web applications, financial transactions, IoT sensors, e-commerce purchases and other sources. Effective data stream processing requires a Big Data analytics tool like Apache Kafka to derive real-time insight and business intelligence from this massive flow of data.

But while Kafka provides a powerful, high-scale, low-latency platform for ingesting and processing live data streams, real-time data ingestion can still be a challenge. Data stream processing can have a negative impact on source systems, may require complex custom development and may be difficult to scale to support the ideal number of data sources.

To enable organizations to take advantage of data stream processing with Apache Kafka, Qlik (Attunity) solves these challenges with efficient, real-time and scalable data ingest from a wide variety of source database systems.

Qlik (Attunity): powerful tools for data stream processing

Qlik (Attunity) is a global leader in data integration and Big Data management. With a software portfolio that accelerates data ingestion, promotes data availability, automates data processes and optimizes data management, Qlik (Attunity) helps companies everywhere derive more value from data while reducing administrative burden and minimizing costs.

As a Big Data solution, Qlik (Attunity) automates data stream processing, enabling real-time data capture by feeding live database changes to Kafka message brokers with low latency. Replicate's log-based change data capture (CDC) technology minimizes the impact on production systems, while a unique zero-footprint architecture eliminates the need to install agents on source database systems.

Qlik (Attunity) also simplifies data stream processing by allowing administrators to use an intuitive GUI to quickly and easily establish data feeds without need for manual coding. The Qlik (Attunity) platform supports the industry's broadest range of sources, including all major RDBMS, data warehouses and mainframe systems. Centralized management capabilities help to simplify execution and monitoring of data stream processing tasks. And a powerful streaming architecture and database streaming software enables organizations to scale easily, ingesting data from hundreds or thousands of databases.

Benefits for data stream processing

With Qlik (Attunity), organizations can manage data stream processing more effectively to:

  • Gain more value from streaming data ingest with Kafka.
  • Support DB streaming by turning databases into live feeds.
  • Accelerating delivery of data to enable real-time analytics.
  • Reduce the skill and training requirements for managing data stream processing.