Dremio vs StreamSets: What are the differences?

# Introduction

1. **Data Processing Paradigm**: Dremio is primarily designed for data analytics and BI use cases, whereas StreamSets is focused on data integration and pipeline orchestration. Dremio provides a SQL interface for querying and analyzing data, while StreamSets offers a visual interface for building data pipelines.
2. **Data Sources**: Dremio supports a wide range of data sources including traditional databases, cloud storage, and data lakes, while StreamSets focuses on ingesting data from diverse sources and transforming it before loading it into destinations.
3. **Real-time Processing**: StreamSets excels in real-time data processing scenarios, enabling users to ingest and process data continuously with low latency, while Dremio is more suited for batch processing and interactive analytics.
4. **Deployment Options**: Dremio can be deployed on-premises, in the cloud, or in hybrid environments, offering flexibility in deployment options, while StreamSets is typically deployed on-premises or in the cloud but lacks hybrid deployment capabilities.
5. **Data Governance and Security**: Dremio provides advanced data governance features such as fine-grained access control and data lineage tracking, ensuring data security and compliance, whereas StreamSets focuses more on data movement and transformation with limited governance features.
6. **Open Source vs. Commercial**: Dremio offers both open-source and commercial editions, providing users with the option to choose based on their requirements, whereas StreamSets is primarily a commercial product with a free version for limited functionality.

In Summary, Dremio and StreamSets differ in their data processing paradigm, supported data sources, real-time processing capabilities, deployment options, data governance features, and licensing models.