The implementation and performance of compressed databases
ACM SIGMOD Record
Query optimization in compressed database systems
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Implementing database operations using SIMD instructions
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Efficient Aggregation Algorithms for Compressed Data Warehouses
IEEE Transactions on Knowledge and Data Engineering
Performing joins without decompression in a compressed database system
ACM SIGMOD Record
C-store: a column-oriented DBMS
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Super-Scalar RAM-CPU Cache Compression
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Integrating compression and execution in column-oriented database systems
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
How to wring a table dry: entropy compression of relations and querying of compressed relations
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Constant-Time Query Processing
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
SIMD-scan: ultra fast in-memory table scan using on-chip vector processing units
Proceedings of the VLDB Endowment
Reordering columns for smaller indexes
Information Sciences: an International Journal
Column-oriented storage techniques for MapReduce
Proceedings of the VLDB Endowment
Efficient transaction processing in SAP HANA database: the end of a column store myth
SIGMOD '12 Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data
Reordering rows for better compression: Beyond the lexicographic order
ACM Transactions on Database Systems (TODS)
A storage advisor for hybrid-store databases
Proceedings of the VLDB Endowment
Sliced column-store (SCS): ontological foundations and practical implications
ER'12 Proceedings of the 31st international conference on Conceptual Modeling
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BI accelerator solutions like the SAP NetWeaver database engine TREX achieve high performance when processing complex analytic queries in large data warehouses. They do so with a combination of column-oriented data organization, memory-based processing, and a scalable multiserver architecture. The use of data compression techniques further reduces both memory consumption and processing time. In this paper we study query operators like scan and aggregation on compressed data structures implemented in TREX.