StreamSets: Modern data integration

Data has become a critical success factor for virtually every aspect of an organization’s strategic goals. Increasing pressure from competitive threats, supply chain and economic volatility, and changing customer expectations, combined with the foundational role data plays in digital transformation initiatives, creates demand for ongoing real-time analytics from stakeholders across the enterprise. 

Meeting these strategic goals requires you to unlock data without ceding control. Specifically, eliminating data integration friction to keep pace with need-it-now business demands. You also need to enable innovation, prototyping, and experimentation with centralized guardrails so you can deploy and manage all aspects of your data flows with requisite controls while enabling teams across the organization. Lastly, you need to insulate your data pipelines from unexpected shifts so you can continue to operate effectively in the face of change.

When you do this, you’ll meet the data integration needs of your end users faster and with fewer resources. You’ll reduce the costs and risks associated with the flow of data across your organization. And you’ll improve real-time decision-making to stay competitive and keep your business relevant. 

Data teams use  the StreamSets data integration platform to bridge the gap between new and legacy environments easily and securely and to see how systems are connected and data is flowing across the enterprise. Resilient and repeatable pipelines ensure data team members at all skill levels thrive in today’s world of constant change. 

Agile reporting

Leverage core enterprise data to improve consistency, accuracy, and depth of reporting. Easily incorporate files through a wealth of legacy data source connectors.

Advanced analytics 

Integrate enterprise and legacy analytic data stores with cloud data platforms for deeper analytics and better decision-making. 

Operational analytics 

Process data “en route” from OLTP sources to cloud data warehouses, providing analytics-ready data that teams rely on for daily operations. 

 Eliminate data integration friction.

• Learn once to create many different integration pipelines. StreamSets single user interface provides the functionality to build and deploy CDC, streaming, ETL, and ELT pipelines for any platform, on-premises or in the cloud.
• With StreamSets Python SDK, you can templatize data pipelines for scale, easily creating hundreds of pipelines with just a few lines of code. The Python SDK hooks within the UI-based tool for programmatic creation and management of pipelines and jobs.
• Simplify all transformations with extensible drag-and-drop processors. With 50 pre-defined processors, you can meet 99% of your analytics requirements out of the box and give your “pro-level” users the ability to include custom code and deliver it as a new element that can be easily reused.

Enable innovation, prototyping, and experimentation with centralized guardrails.

• StreamSets’ hybrid deployment with centralized engine management easily and securely bridges the gap between new and legacy environments. With a data “mission control” across all environments, you can easily move between clouds and on-premises.
• Topologies show how systems are connected and how data is flowing across the enterprise. StreamSets provides visibility into data connections and flows across a hybrid landscape, including volume and throughput of data, as well as exactly what data is moving between components.
• Data SLAs and rules expose hidden problems in data flows. Auto-notifications based on user-defined triggers throughout data pipelines for data quality, sizing, throughput performance, error rates, private/sensitive information leakage, and more, with alerts that can be sent via email, Slack, or other system messages.

Insulate your data pipelines from unexpected shifts.

• StreamSets’ dynamic pipelines allow you to introduce change without worrying about breakage. They proactively adapt to change by monitoring, alerting, and taking prescriptive action to keep your data flowing. Ingest more data without building more infrastructure, and enable line of business agility without repercussions to the data engineering team.
• Pipeline fragments easily capture, reuse, and refine business logic. Encapsulate expert knowledge in portable, shareable elements and keep them up to date no matter where they are used. Common transformation logic and processing elements can be independently reused across multiple pipelines without specialized knowledge.
• Flexibly run your data pipelines in any cloud provider or on-premises environment with infrastructure change management, helping teams take full advantage of their preferred cloud platforms or specialized cloud data services that best fit their requirements.