Data-Centric Serverless Computing with LambdaStore

LambdaStore is a data-centric serverless platform that breaks the split between stateless functions and external storage in classic cloud computing platforms. By scheduling serverless invocations near data instead of pulling data to compute, LambdaStore substantially reduces the state access cost that dominates today’s serverless workloads. Leveraging its transactional storage engine, LambdaStore delivers serializable guarantees and exactly-once semantics across chains of lambda invocations—a capability missing in current Function-as-a-Service offerings. We make three key contributions: (1) an object-oriented programming model that ties function invocations with its data; (2) a transaction layer with adaptive lock granularity and an optimistic concurrency control protocol designed for serverless workloads to keep contention low while preserving serializability; and (3) an elastic storage system that preserves the elasticity of the serverless paradigm while lambda functions run close to their data. Under read-heavy workloads, LambdaStore lifts throughput by orders of magnitude over existing serverless platforms while holding end-to-end latency below 20 ms.

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Publication Details

Journal
Software
Published
2026-01-21
DOI
https://doi.org/10.3390/software5010005
Primary Topic
Distributed systems and fault tolerance
Type
article
Field-Weighted Citation Impact
0.00

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article

Data-Centric Serverless Computing with LambdaStore

Kai Mast, Aditya Jain, Andrea Arpaci-Dusseau, Remzi Arpaci-Dusseau et al.
Software
Distributed systems and fault tolerance
article

Data-Centric Serverless Computing with LambdaStore

Kai Mast, Aditya Jain, Andrea Arpaci-Dusseau, Remzi Arpaci-Dusseau, Suyan Qu
article en

Abstract

LambdaStore is a data-centric serverless platform that breaks the split between stateless functions and external storage in classic cloud computing platforms. By scheduling serverless invocations near data instead of pulling data to compute, LambdaStore substantially reduces the state access cost that dominates today’s serverless workloads. Leveraging its transactional storage engine, LambdaStore delivers serializable guarantees and exactly-once semantics across chains of lambda invocations—a capability missing in current Function-as-a-Service offerings. We make three key contributions: (1) an object-oriented programming model that ties function invocations with its data; (2) a transaction layer with adaptive lock granularity and an optimistic concurrency control protocol designed for serverless workloads to keep contention low while preserving serializability; and (3) an elastic storage system that preserves the elasticity of the serverless paradigm while lambda functions run close to their data. Under read-heavy workloads, LambdaStore lifts throughput by orders of magnitude over existing serverless platforms while holding end-to-end latency below 20 ms.

SoftwareVol. 5(1)
University of Nevada, Reno (US), University of Wisconsin–Madison (US)
National Science Foundation
Openalex Percentile: Top 85%
Distributed systems and fault tolerance
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