Physical integrity in a large segmented database
ACM Transactions on Database Systems (TODS)
Main Memory Database Systems: An Overview
IEEE Transactions on Knowledge and Data Engineering
Checkpointing Memory-Resident Databases
Proceedings of the Fifth International Conference on Data Engineering
OLTP through the looking glass, and what we found there
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
H-store: a high-performance, distributed main memory transaction processing system
Proceedings of the VLDB Endowment
A common database approach for OLTP and OLAP using an in-memory column database
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Schism: a workload-driven approach to database replication and partitioning
Proceedings of the VLDB Endowment
The mixed workload CH-benCHmark
Proceedings of the Fourth International Workshop on Testing Database Systems
Fast checkpoint recovery algorithms for frequently consistent applications
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Efficiently compiling efficient query plans for modern hardware
Proceedings of the VLDB Endowment
HyPer: A hybrid OLTP&OLAP main memory database system based on virtual memory snapshots
ICDE '11 Proceedings of the 2011 IEEE 27th International Conference on Data Engineering
DaMoN '12 Proceedings of the Eighth International Workshop on Data Management on New Hardware
Compacting transactional data in hybrid OLTP&OLAP databases
Proceedings of the VLDB Endowment
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The quest for real-time business intelligence requires executing mixed transaction and query processing workloads on the same current database state. However, as Harizopoulos et al. [6] showed for transactional processing, co-execution using classical concurrency control techniques will not yield the necessary performance -- even in re-emerging main memory database systems. Therefore, we designed an in-memory database system that separates transaction processing from OLAP query processing via periodically refreshed snapshots. Thus, OLAP queries can be executed without any synchronization and OLTP transaction processing follows the lock-free, mostly serial processing paradigm of H-Store [8]. In this paper, we analyze different snapshot mechanisms: Hardware-supported Page Shadowing, which lazily copies memory pages when changed by transactions, software controlled Tuple Shadowing, which generates a new version when a tuple is modified, software controlled Twin Tuple, which constantly maintains two versions of each tuple and HotCold Shadowing, which effectively combines Tuple Shadowing and hardware-supported Page Shadowing by clustering update-intensive objects. We evaluate their performance based on the mixed workload CH-BenCHmark which combines the TPC-C and the TPC-H benchmarks on the same database schema and state.