StreamSets

Founded by Girish Pancha & Arvind Prabhakar in 2014

Build and deploy streaming data pipelines across multicloud environments without writing code

Pricing model

Free Trial, Paid

Rating

★ Neutral

Time to value

< 10 Hours

You can use IBM StreamSets to design, deploy, and manage streaming data pipelines across cloud and on-premises environments. It provides a visual drag-and-drop designer alongside a Python SDK, allowing your engineering team to ingest structured, semi-structured, and unstructured data without writing custom connection scripts. The system automatically detects and handles data drift, preventing pipeline failures when source schemas change unexpectedly. You can feed real-time event streams into analytics engines, machine learning models, and centralized data warehouses to support fraud detection, customer personalization, and operational monitoring.

What StreamSets does

Build visual data ingestion pipelines using prebuilt connectorsConfigure automated rules to process schema drift without breaking jobsDeploy pipeline workloads to virtual private clouds or local infrastructureWrite Python scripts to automate pipeline creation and orchestrationAggregate live log events from web servers and IoT sensorsStream structured and unstructured records into analytics repositoriesTest pipeline configurations using an interactive demo environmentDrag-and-drop visual interface for creating streaming pipelinesAutomatic detection and handling of unexpected schema changes and data driftPython SDK for building, deploying, and automating pipelines using codeCross-cloud deployment across AWS, Azure, Google Cloud, and local serversContinuous ingestion of structured, semi-structured, and unstructured data streamsPrebuilt processors to clean, filter, and transform live event streamsDirect integration with enterprise analytics and machine learning repositories

Pricing breakdown

Pricing model: Free Trial, Paid

Frequently asked

AWS

Microsoft Azure

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