Bauplan: zero-copy, scale-up FaaS for data pipelines

TL;DR

Bauplan introduces a specialized FaaS model optimized for data pipelines, enabling declarative DAGs and efficient execution, thus improving performance and developer experience for data workloads.

Contribution

It presents bauplan, a novel FaaS programming model tailored for data pipelines that reduces generality to enhance data-awareness and efficiency.

Findings

Achieves better performance on data workloads

Provides a more developer-friendly experience

Efficient execution of declarative DAGs

Abstract

Chaining functions for longer workloads is a key use case for FaaS platforms in data applications. However, modern data pipelines differ significantly from typical serverless use cases (e.g., webhooks and microservices); this makes it difficult to retrofit existing pipeline frameworks due to structural constraints. In this paper, we describe these limitations in detail and introduce bauplan, a novel FaaS programming model and serverless runtime designed for data practitioners. bauplan enables users to declaratively define functional Directed Acyclic Graphs (DAGs) along with their runtime environments, which are then efficiently executed on cloud-based workers. We show that bauplan achieves both better performance and a superior developer experience for data workloads by making the trade-off of reducing generality in favor of data-awareness