| 20 |
C-Store: A Column-oriented DBMS |
2005 |
VLDB |
0.00086163998 |
| 132 |
Integrating Compression and Execution in Column-Oriented Database Systems |
2006 |
SIGMOD |
0.00043697853 |
| 230 |
A Performance Evaluation of Four Parallel Join Algorithms in a Shared-Nothing Multiprocessor Environment |
1989 |
SIGMOD |
0.00032145125 |
| 307 |
SIMD-Scan: Ultra Fast in-Memory Table Scan using on-Chip Vector Processing Units |
2009 |
VLDB |
0.00028226342 |
| 343 |
Implementing Database Operations Using SIMD Instructions |
2002 |
SIGMOD |
0.00026756534 |
| 359 |
On the Power of Magic |
1987 |
PODS |
0.00025830228 |
| 771 |
Relational Joins on Graphics Processors |
2008 |
SIGMOD |
0.00016813054 |
| 959 |
Rethinking SIMD Vectorization for In-Memory Databases |
2015 |
SIGMOD |
0.00015034808 |
| 1,267 |
BitWeaving: Fast Scans for Main Memory Data Processing |
2013 |
SIGMOD |
0.00012917585 |
| 1,271 |
The Yin and Yang of Processing Data Warehousing Queries on GPU Devices |
2013 |
VLDB |
0.00012900735 |
| 1,285 |
Hardware-Oblivious Parallelism for In-Memory Column-Stores |
2013 |
VLDB |
0.00012809552 |
| 1,622 |
Row-wise Parallel Predicate Evaluation |
2008 |
VLDB |
0.00011104582 |
| 2,019 |
Voodoo - A Vector Algebra for Portable Database Performance on Modern Hardware |
2016 |
VLDB |
9.7814175e-05 |
| 2,044 |
A Study of the Fundamental Performance Characteristics of GPUs and CPUs for Database Analytics |
2020 |
SIGMOD |
9.6963999e-05 |
| 2,292 |
Pipelined Query Processing in Coprocessor Environments |
2018 |
SIGMOD |
9.0884645e-05 |
| 2,390 |
ByteSlice: Pushing the Envelop of Main Memory Data Processing with a New Storage Layout |
2015 |
SIGMOD |
8.9006978e-05 |
| 2,659 |
HetExchange: Encapsulating heterogeneous CPU-GPU parallelism in JIT compiled engines |
2019 |
VLDB |
8.3615158e-05 |
| 2,890 |
Database Compression on Graphics Processors |
2010 |
VLDB |
7.9586083e-05 |
| 3,161 |
A Memory Bandwidth-Efficient Hybrid Radix Sort on GPUs |
2017 |
SIGMOD |
7.4648665e-05 |
| 3,260 |
Query Processing on Tensor Computation Runtimes |
2022 |
VLDB |
7.3091312e-05 |
| 3,899 |
Efficient Join Algorithms For Large Database Tables in a Multi-GPU Environment |
2021 |
VLDB |
6.6513982e-05 |
| 4,000 |
MG-Join: A Scalable Join for Massively Parallel Multi-GPU Architectures |
2021 |
SIGMOD |
6.5419402e-05 |
| 4,089 |
In-Cache Query Co-Processing on Coupled CPU-GPU Architectures |
2015 |
VLDB |
6.4559891e-05 |
| 4,272 |
Looking Ahead Makes Query Plans Robust: Making the Initial Case with In-Memory Star Schema Data Warehouse Workloads |
2017 |
VLDB |
6.2933353e-05 |
| 4,520 |
The FastLanes Compression Layout: Decoding >100 Billion Integers per Second with Scalar Code |
2023 |
VLDB |
6.1119645e-05 |
| 5,018 |
Orchestrating Data Placement and Query Execution in Heterogeneous CPU-GPU DBMS |
2022 |
VLDB |
5.7503878e-05 |
| 5,039 |
Tile-based Lightweight Integer Compression in GPU |
2022 |
SIGMOD |
5.7369993e-05 |
| 5,195 |
Bitvector-aware Query Optimization for Decision Support Queries |
2020 |
SIGMOD |
5.6314278e-05 |
| 5,303 |
Applying Hash Filters To Improving The Execution Of Bushy Trees |
1993 |
VLDB |
5.5740327e-05 |
| 5,772 |
Predicate Transfer: Efficient Pre-Filtering on Multi-Join Queries |
2024 |
CIDR |
5.3313794e-05 |
| 5,826 |
Towards a Hybrid Design for Fast Query Processing in DB2 with BLU Acceleration Using Graphical Processing Units: A Technology Demonstration |
2016 |
SIGMOD |
5.3116062e-05 |
| 6,068 |
GPU Database Systems Characterization and Optimization |
2024 |
VLDB |
5.2240241e-05 |
| 6,220 |
Distributed GPU Joins on Fast RDMA-capable Networks |
2023 |
SIGMOD |
5.1446966e-05 |
| 6,367 |
Improving Execution Efficiency of Just-in-time Compilation based Query Processing on GPUs |
2021 |
VLDB |
5.0887599e-05 |
| 6,605 |
MotherDuck: DuckDB in the cloud and in the client |
2024 |
CIDR |
4.9923144e-05 |
| 7,427 |
Selection Pushdown in Column Stores using Bit Manipulation Instructions |
2023 |
SIGMOD |
4.7282014e-05 |
| 8,410 |
Pruning in Snowflake: Working Smarter, Not Harder |
2025 |
SIGMOD |
4.5154358e-05 |
| 8,502 |
New Query Optimization Techniques in the Spark Engine of Azure Synapse |
2022 |
VLDB |
4.491819e-05 |
| 8,846 |
Scaling your Hybrid CPU-GPU DBMS to Multiple GPUs |
2024 |
VLDB |
4.432948e-05 |
| 9,694 |
Share the Tensor Tea: How Databases can Leverage the Machine Learning Ecosystem |
2022 |
VLDB |
4.2984337e-05 |