AI Summary of Peer-Reviewed Research

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gRPC was fastest for large read operations in comparison test

Six server rack enclosures arranged in a 2x3 grid configuration displaying illuminated orange and red network cables with blue indicator lights, typical of data center infrastructure.
Research area:Computer ScienceWeb applicationRelational database

What the study found: The study found that gRPC was the fastest option for large-scale read operations, while GraphQL and Thrift were faster when operations moved small amounts of data.

Why the authors say this matters: The authors present this comparison as a performance study of web programming interfaces and suggest that the findings can help distinguish how GraphQL, gRPC, and Thrift behave under different data sizes.

What the researchers tested: The researchers built three applications, each using one of the three technologies: GraphQL, gRPC, and Thrift. They tested the applications with JMeter, a tool for load testing, and measured execution time and the amount of data returned during operations on a relational database.

What worked and what didn't: gRPC showed the shortest execution time for large-scale read operations. GraphQL and Thrift performed faster for operations that transported small volumes of data.

What to keep in mind: The abstract does not describe additional limitations, beyond the comparison being based on three developed applications, JMeter testing, and relational-database operations.

Key points

  • The study compared GraphQL, gRPC, and Thrift.
  • gRPC was fastest for large-scale read operations.
  • GraphQL and Thrift were faster for operations with small data volumes.
  • The applications were tested with JMeter.
  • Execution time and returned data volume were measured on a relational database.

Disclosure

Research title:
gRPC was fastest for large read operations in comparison test
Authors:
Piotr Rożek, Mariusz Dzieńkowski
Institutions:
Lublin University of Technology
Publication date:
2026-03-30
OpenAlex record:
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AI provenance: This post was generated by OpenAI. The original authors did not write or review this post.