Apache Calcite: A Foundational Framework for Optimized Query Processing Over Heterogeneous Data Sources
Summary: Apache Calcite is an embeddable framework for query processing and optimization over heterogeneous data sources. Modular optimizer with many rules and extensible adapters enables embedding in Hive, Flink, Druid, Storm, supporting relational, streaming data. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Edmon Begoli (Oak Ridge National Laboratory)
- 2. Jesús Camacho-Rodríguez (Hortonworks)
- 3. Julian Hyde (Hortonworks)
- 4. Michael J. Mior (University of Waterloo)
- 5. Daniel Lemire (University of Quebec)
BibTeX Citation
@inproceedings{begoli_sigmod18,
title = {{Apache Calcite: A Foundational Framework for Optimized Query Processing Over Heterogeneous Data Sources}},
author = {Begoli, Edmon and Camacho-Rodríguez, Jesús and Hyde, Julian and Mior, Michael J. and Lemire, Daniel},
series = {{SIGMOD} '18},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3183713.3190662},
url = {https://dl.acm.org/doi/10.1145/3183713.3190662},
year = {2018}
}Incoming Citations (Sorted by Pagerank)
Showing 24 of 74 citing papers.
Outgoing Citations (Sorted by Pagerank)
Showing 13 of 13 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 4,069 | Dynamically Optimizing Queries over Large Scale Data Platforms | 2014 | SIGMOD |
| 2 | 8,014 | AJoin: Ad-hoc Stream Joins at Scale | 2020 | VLDB |
| 3 | 9,254 | QMapper for Smart Grid: Migrating SQL-based Application to Hive | 2015 | SIGMOD |
| 4 | 31 | Hive - A Warehousing Solution Over a Map-Reduce Framework | 2009 | VLDB |
| 5 | 8,004 | A Spark Optimizer for Adaptive, Fine-Grained Parameter Tuning | 2024 | VLDB |
| 6 | 4,884 | One SQL to Rule Them All – an Efficient and Syntactically Idiomatic Approach to Management of Streams and Tables | 2019 | SIGMOD |
| 7 | 5,348 | Adaptive and Robust Query Execution for Lakehouses at Scale | 2024 | VLDB |
| 8 | 2,689 | Major Technical Advancements in Apache Hive | 2014 | SIGMOD |
| 9 | 6,576 | Towards Query Optimizer as a Service (QOaaS) in a Unified LakeHouse Ecosystem: Can One QO Rule Them All? | 2025 | CIDR |
| 10 | 3,446 | Apache Hive: From MapReduce to Enterprise-grade Big Data Warehousing | 2019 | SIGMOD |