Instant Loading for Main Memory Databases
Summary: Instant Loading delivers wire-speed CSV bulk loading for main-memory DBs by optimizing load phases on multi-core CPUs. A single-node data-staging model with instantaneous load-work-unload cycles across archives enables rapid in-memory loading and fast subsequent queries. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Tobias Muehlbauer
- 2. Wolf Roediger
- 3. Robert Seilbeck
- 4. Angelika Reiser
- 5. Alfons Kemper
- 6. Thomas Neumann
Incoming Citations (Sorted by Pagerank)
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Outgoing Citations (Sorted by Pagerank)
Showing 17 of 17 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,742 | Databases in the Era of Memory-Centric Computing | 2025 | CIDR | 4.2856385e-05 |
| 3,548 | Adaptive Query Processing on RAW Data | 2014 | VLDB | 6.9798836e-05 |
| 52 | Database Architecture Optimized for the new Bottleneck: Memory Access | 1999 | VLDB | 0.00066322421 |
| 3,035 | Instant Recovery for Main-Memory Databases | 2015 | CIDR | 7.6724794e-05 |
| 1,346 | NoDB: Efficient Query Execution on Raw Data Files | 2012 | SIGMOD | 0.00012472598 |
| 2,367 | Here are my Data Files. Here are my Queries. Where are my Results? | 2011 | CIDR | 8.9502761e-05 |
| 2,975 | Parallel In-Situ Data Processing with Speculative Loading | 2014 | SIGMOD | 7.7871791e-05 |
| 2,976 | In-Memory Performance for Big Data | 2015 | VLDB | 7.7865451e-05 |
| 6,668 | Mainlining Databases: Supporting Fast Transactional Workloads on Universal Columnar Data File Formats | 2021 | VLDB | 4.9647176e-05 |
| 9,917 | Shared Load(ing): Efficient Bulk Loading into Optimized Storage | 2020 | CIDR | 4.2520778e-05 |