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Procella: Unifying serving and analytical data at YouTube
Summary: Procella unifies serving and analytics in a single SQL engine, enabling reporting, dashboards, embedded stats, and time-series monitoring without silos. A YouTube-scale SQL engine handling hundreds of billions of queries daily in a single product.
(summarized by gpt-5-nano on Feb 09 2026)
- Paper ID
- 11924
- Venue
- VLDB
- Year
- 2019
- Pagerank
- 0.00010019433
- Overall Rank
- 1,939 | 86.53%
- DOI
-
10.14778/3352063.3352121
Incoming Non-self Citations Over Time
Incoming Citations (Sorted by Pagerank)
Showing 26 of 26 citing papers.
| Rank |
Citing Paper |
Year |
Venue |
Pagerank |
| 2,060 |
Dremel: A Decade of Interactive SQL Analysis at Web Scale |
2020 |
VLDB |
9.6585115e-05 |
| 3,764 |
F1 Lightning: HTAP as a Service |
2020 |
VLDB |
6.7762323e-05 |
| 4,240 |
Db2 Event Store: A Purpose-Built IoT Database Engine |
2020 |
VLDB |
6.3258697e-05 |
| 4,509 |
ALP: Adaptive Lossless floating-Point Compression |
2023 |
SIGMOD |
6.1251244e-05 |
| 4,516 |
An Empirical Evaluation of Columnar Storage Formats |
2024 |
VLDB |
6.1146215e-05 |
| 4,520 |
The FastLanes Compression Layout: Decoding >100 Billion Integers per Second with Scalar Code |
2023 |
VLDB |
6.1119645e-05 |
| 4,665 |
Napa: Powering Scalable Data Warehousing with Robust Query Performance at Google |
2021 |
VLDB |
6.0057914e-05 |
| 5,011 |
SQL Has Problems. We Can Fix Them: Pipe Syntax In SQL |
2024 |
VLDB |
5.7544221e-05 |
| 5,020 |
Adaptive HTAP through Elastic Resource Scheduling |
2020 |
SIGMOD |
5.7482116e-05 |
| 5,537 |
Presto: A Decade of SQL Analytics at Meta |
2023 |
SIGMOD |
5.453017e-05 |
| 5,691 |
Cloud-Native Transactions and Analytics in SingleStore |
2022 |
SIGMOD |
5.3697521e-05 |
| 6,397 |
BigLake: BigQuery’s Evolution toward a Multi-Cloud Lakehouse |
2024 |
SIGMOD |
5.0749432e-05 |
| 7,461 |
Scalable Multi-Query Execution using Reinforcement Learning |
2021 |
SIGMOD |
4.7193668e-05 |
| 7,470 |
Bullion: A Column Store for Machine Learning |
2025 |
CIDR |
4.7159125e-05 |
| 7,491 |
Krypton: Real-time Serving and Analytical SQL Engine at ByteDance |
2023 |
VLDB |
4.7135369e-05 |
| 9,105 |
Meta's Next-generation Realtime Monitoring and Analytics Platform |
2022 |
VLDB |
4.3911131e-05 |
| 9,646 |
The FastLanes File Format |
2025 |
VLDB |
4.3067693e-05 |
| 9,907 |
Keep Your Distributed Data Warehouse Consistent at a Minimal Cost |
2023 |
SIGMOD |
4.2536148e-05 |
| 9,980 |
Survivorship Bias in Industrial Database Workloads |
2026 |
CIDR |
4.1905499e-05 |
| 10,220 |
FlatStor: An Efficient Embedded-Index Based Columnar Data Layout for Multimodal Data Workloads |
2026 |
VLDB |
4.1905499e-05 |
| 10,384 |
Data Chunk Compaction in Vectorized Execution |
2025 |
SIGMOD |
4.1905499e-05 |
| 10,777 |
Unlocking the Power of CI/CD for Data Pipelines in Distributed Data Warehouses |
2025 |
VLDB |
4.1905499e-05 |
| 11,093 |
Simple (yet Efficient) Function Authoring for Vectorized Engines |
2024 |
VLDB |
4.1905499e-05 |
| 11,199 |
QaaD (Query-as-a-Data): Scalable Execution of Massive Number of Small Queries in Spark |
2023 |
SIGMOD |
4.1905499e-05 |
| 11,214 |
SH2O: Efficient Data Access for Work-Sharing Databases |
2023 |
SIGMOD |
4.1905499e-05 |
| 11,489 |
Real-time Data Infrastructure at Uber |
2021 |
SIGMOD |
4.1905499e-05 |
Outgoing Citations (Sorted by Pagerank)
Showing 16 of 16 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank |
Cited Paper |
Year |
Venue |
Pagerank |
| 66 |
Spark SQL: Relational Data Processing in Spark |
2015 |
SIGMOD |
0.00061707583 |
| 109 |
Dremel: Interactive Analysis of Web-Scale Datasets |
2010 |
VLDB |
0.00048217028 |
| 132 |
Integrating Compression and Execution in Column-Oriented Database Systems |
2006 |
SIGMOD |
0.00043697853 |
| 160 |
Automated Selection of Materialized Views and Indexes for SQL Databases |
2000 |
VLDB |
0.00040053897 |
| 167 |
The Snowflake Elastic Data Warehouse |
2016 |
SIGMOD |
0.00039408116 |
| 211 |
Gorilla: A Fast, Scalable, In-Memory Time Series Database |
2015 |
VLDB |
0.0003401421 |
| 424 |
Amazon Redshift and the Case for Simpler Data Warehouses |
2015 |
SIGMOD |
0.00023604384 |
| 959 |
Rethinking SIMD Vectorization for In-Memory Databases |
2015 |
SIGMOD |
0.00015034808 |
| 1,470 |
Processing a Trillion Cells per Mouse Click |
2012 |
VLDB |
0.00011827274 |
| 1,588 |
Druid: A Real-time Analytical Data Store |
2014 |
SIGMOD |
0.00011232949 |
| 1,838 |
Mesa: Geo-Replicated, Near Real-Time, Scalable Data Warehousing |
2014 |
VLDB |
0.00010353323 |
| 2,334 |
Orion 2.0: Native Support for Uncertain Data |
2008 |
SIGMOD |
9.01132e-05 |
| 3,344 |
F1 Query: Declarative Querying at Scale |
2018 |
VLDB |
7.1944106e-05 |
| 3,428 |
Distributed Join Algorithms on Thousands of Cores |
2017 |
VLDB |
7.1002401e-05 |
| 4,128 |
Advanced Join Strategies for Large-Scale Distributed Computation |
2014 |
VLDB |
6.4214449e-05 |
| 5,657 |
FluxQuery: An Execution Framework for Highly Interactive Query Workloads |
2016 |
SIGMOD |
5.3873634e-05 |
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Presto: A Decade of SQL Analytics at Meta |
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| 6,100 |
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| 4,665 |
Napa: Powering Scalable Data Warehousing with Robust Query Performance at Google |
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