Cloud data teams are faced with a continuity problem rather than a simple data movement challenge. In the past, ETL pipelines were designed to transfer data from one system to another on a fixed schedule. However, in modern cloud environments, this approach is no longer sufficient.
The article discusses the top 5 streaming ETL tools for cloud data teams. Each tool is evaluated based on its strengths and suitability for different team requirements. From Artie, which focuses on continuous, CDC-first data movement, to Fivetran, known for its managed ingestion and operational consistency, each tool offers unique features that cater to specific needs.
Airbyte is highlighted as a flexible platform that provides more control and architectural freedom to engineering teams. On the other hand, Hevo Data is designed for teams seeking streaming-style freshness without complex operations. Matillion, while not a pure streaming ETL platform, excels in transformation and orchestration close to the warehouse.
The article emphasizes that streaming ETL is not just about speed but about maintaining continuity in data operations. It discusses the core primitives that define a strong streaming ETL platform, such as change data capture, schema evolution handling, observability, recovery mechanisms, and aligning the operational model with the team’s needs.
Ultimately, the choice of a streaming ETL tool should be a long-term decision that considers how data systems will adapt to ongoing changes as organizations grow. The focus should be on sustaining correctness amidst increasing volumes, evolving schemas, and expanding business-critical workflows.
