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Palette: Enabling Scalable Analytics for Big-Memory, Multicore Machines

Summary: Palette enables in-memory analytics on big NUMA multicore machines with multiple input representations, trading space for time. A cost-based selector automatically picks the fastest operator while preserving Hadoop APIs; demos cover creation and auto-selection. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4816
Venue
SIGMOD
Year
2014
Pagerank
4.1945683e-05
Overall Rank
11,972 | 16.72%
DOI
10.1145/2588555.2594509

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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
87 Hekaton: SQL Server’s Memory-Optimized OLTP Engine 2013 SIGMOD 0.00052389723
404 Multi-Core, Main-Memory Joins: Sort vs. Hash Revisited 2014 VLDB 0.00024143076
3,504 M3R: Increased Performance for In-Memory Hadoop Jobs 2012 VLDB 7.0347515e-05
7,511 Hone: "Scaling Down" Hadoop on Shared-Memory Systems 2013 VLDB 4.7180617e-05
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