Abstract
Over the last two releases SQL Server has integrated two specialized engines into the core system: the Apollo column store engine for analytical workloads and the Hekaton in-memory engine for high-performance OLTP workloads. There is an increasing demand for real-time analytics, that is, for running analytical queries and reporting on the same system as transaction processing so as to have access to the freshest data. SQL Server 2016 will include enhancements to column store indexes and in-memory tables that significantly improve performance on such hybrid workloads. This paper describes four such enhancements: column store indexes on in-memory tables, making secondary column store indexes on disk-based tables updatable, allowing B-tree indexes on primary column store indexes, and further speeding up the column store scan oper ator.
- Kalen Delaney, SQL Server In-Memory OLTP Internals Overview, Red gate books, 2014.Google Scholar
- Cristian Diaconu, Craig Freedman, Erik Ismert, Per-Åke Larson, Pravin Mittal, Ryan Stonecipher, Nitin Verma, Mike Zwilling: Hekaton: SQL server's memory-optimized OLTP engine. SIGMOD 2013: 1243--1254 Google Scholar
- Craig Freedman, Erik Ismert, Per-Åke Larson: Compilation in the Microsoft SQL Server Hekaton Engine. IEEE Data Engeenering. Bulletin 37(1): 22--30 (2014)Google Scholar
- IBM, IBM DB2 Analytics Accelerator for z/OS, http://www03.ibm.com/software/products/en/db2analacceforzosGoogle Scholar
- IBM, Informix Warehouse, http://www-01.ibm.com/software/data/informix/warehouse/Google Scholar
- Alfons Kemper et. al., Processing in the Hybrid OLTP & OLAP Main-Memory Database System HyPer. IEEE Data Engineering Bulletin 36(2): 41--47 (2013)Google Scholar
- Per-Åke Larson, Cipri Clinciu, Eric N. Hanson, Artem Oks, Susan L. Price, Srikumar Rangarajan, Aleksandras Surna, Qingqing Zhou: SQL server column store indexes. SIGMOD 2011: 1177--1184 Google Scholar
- Per-Åke Larson, Spyros Blanas, Cristian Diaconu, Craig Freedman, Jignesh M. Patel, Mike Zwilling: High-Performance Concurrency Control Mechanisms for Main-Memory Databases. PVLDB 5(4): 298--309 (2011) Google Scholar
- Per-Åke Larson, Cipri Clinciu, Campbell Fraser, Eric N. Hanson, Mostafa Mokhtar, Michal Nowakiewicz, Vassilis Papadimos, Susan L. Price, Srikumar Rangarajan, Remus Rusanu, Mayukh Saubhasik: Enhancements to SQL server column stores. SIGMOD 2013: 1159--1168 Google Scholar
- Justin J. Levandoski, David B. Lomet, Sudipta Sengupta: The Bw-Tree: A B-tree for new hardware platforms. ICDE 2013: 302--313 Google Scholar
- Memsql database, http://www.memsql.com/product/Google Scholar
- Microsoft, In-Memory OLTP (In-Memory Optimization), http://msdn.microsoft.com/en-us/library/dn133186.aspxGoogle Scholar
- Microsoft, Columnstore Indexes Described, http://msdn.microsoft.com/en-us/library/gg492088.aspxGoogle Scholar
- Oracle, Oracle Database In-Memory, http://www.oracle.com/technetwork/database/in-memory/overview/twp-oracle-database-in-memory-2245633.htmlGoogle Scholar
- Pivotal Greenplum Database, http://pivotal.io/big-data/pivotal-greenplum-databaseGoogle Scholar
- Vijayshankar Raman et. Al., DB2 with BLU Acceleration: So Much More than Just a Column Store. PVLDB 6(11): 1080--1091 (2013) Google Scholar
- SAP HANA, http://hana.sap.com/abouthana.htmlGoogle Scholar
- Teradata 14 Hybrid Columnar, http://www.teradata.com/Resources/White-Papers/Teradata-14-Hybrid-ColumnarGoogle Scholar
Index Terms
- Real-time analytical processing with SQL server
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