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Integration for Data Lakes and Warehouses

Power your modern analytics with continuous data ingestion and ETL at scale

You Need Data Now, Not Later

Modern analytics, data science, AI, machine learning…your analysts, data scientists and business innovators are ready to change the world. If you can’t deliver the data they need, faster and with confidence, they’ll find a way around you. (They probably already have.)

The challenge to the provisioning of continuous data is the unexpected, unannounced, and unending changes to data that constantly disrupt dataflow. That’s data drift, and it’s the reason why, sometimes when you go fast, things break. But when you take your time, you fall behind.  

The StreamSets DataOps Advantage

StreamSets offers a powerful, yet simple DataOps Platform to speed data integration for data lakes and data warehouses. Building and operating smart data pipelines drive value to data lakes and enrich data warehouse architectures.

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Data Integration For Data Lakes And Data Warehouses
Design data processing and enrichment flows with a no code, visual interface
Automate serving clean data sets that are fully drift aware
Build real-time data streams for analyzing events and proactive analytics

Flexible Hybrid and Multi-cloud Architecture

Easily migrate your work to the next data platform or cloud infrastructure that rises to the top. 

Data Integration For Data Lakes On AWS
Data Integration For Data Lakes On Azure
Data Integration For Data Lakes And Databricks
Data Integration For Data Lakes And Snowflake
Data Integration For Data Lakes And Cloudera
Data Integration For Data Lakes Google Cloud Platform

How It Works

Rapid Data Ingestion

StreamSets Data Collector delivers the right data the right way into your data lake or data store. Drag-and-drop from a rich library of connectors and components in support of a variety of dataflow patterns:

  • Streaming data ingestion
  • Edge data shipping
  • Change data capture
  • Bulk data loading
  • Micro-batch integration
White Paper: 12 Best Practices for Modern Data Ingestion
Rapid Data Ingestion To Data Lakes And Data Warehouses

Powerful Data Transformation

StreamSets Transformer provides Apache Spark-native transformation and data processing for ETL and machine learning workloads, all without needing to hand code. Aggregate, standardize, and cleanse data during integration or in a data lake or other raw data storage. 

Analyst Report: DataOps Platform with Spark-based Execution
Powerful Data Transformation For Data Lakes And Data Warehouses

Operationalize and Scale Data Pipelines

StreamSets Control Hub gives you one place to monitor and manage all your pipelines, regardless of design pattern or where the workload is being executed. Sleep easy at night with end-to-end real-time dashboards into data flows across your enterprise, enforceable data performance SLAs, and security policies for your data in motion.

Watch: StreamSets Transformer + Control Hub
Operationalize And Scale Data Pipelines For Data Lakes And Data Warehouses
Analyst Report

Gartner Report: 2020 Planning Guide for Data Management

This new Planning Guide from Gartner highlights the innovations and technologies to keep your eye on in 2020.
Webinar

Pipeline Design for Critical Cloud Workloads to Delta Lake

White Paper

12 Best Practices for Modern Data Ingestion

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