Abstract
In this demo we will prove that it is - against common belief - indeed possible to build a main-memory database system that achieves world-record transaction processing throughput and best-of-breed OLAP query response times in one system in parallel on the same database state. The two workloads of online transaction processing (OLTP) and online analytical processing (OLAP) present different challenges for database architectures. Currently, users with high rates of mission-critical transactions have split their data into two separate systems, one database for OLTP and one so-called data warehouse for OLAP. While allowing for decent transaction rates, this separation has many disadvantages including data freshness issues due to the delay caused by only periodically initiating the Extract Transform Load-data staging and excessive resource consumption due to maintaining two separate information systems. We present an efficient hybrid system, called HyPer, that can handle both OLTP and OLAP simultaneously by using hardware-assisted replication mechanisms to maintain consistent snapshots of the transactional data. HyPer is a main-memory database system that guarantees the full ACID properties for OLTP transactions and executes OLAP query sessions (multiple queries) on arbitrarily current and consistent snapshots. The utilization of the processor-inherent support for virtual memory management (address translation, caching, copy-on-write) yields both at the same time: unprecedentedly high transaction rates as high as 100,000+ transactions per second and very fast OLAP query response times on a single system executing both workloads in parallel. The performance analysis is based on a combined TPC-C and TPC-H benchmark.
Original language | English |
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Pages (from-to) | 1367-1370 |
Number of pages | 4 |
Journal | Proceedings of the VLDB Endowment |
Volume | 4 |
Issue number | 12 |
State | Published - Aug 2011 |