HyPer-sonic Combined Transaction AND Query Processing

نویسندگان

  • Florian Funke
  • Alfons Kemper
  • Thomas Neumann
چکیده

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.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

On Scalable and Flexible Transaction and Query Processing in Main-Memory Database Systems

The hardware landscape for database systems has changed dramatically over the past two decades. Today, the traditional database system architecture that was pioneered by System R and is implemented by IBM DB2, Microsoft SQL Server, Oracle and Postgres, shows weaknesses in all major areas of application of commercial database systems: operational transaction processing, decision support and busi...

متن کامل

HyPer: Adapting Columnar Main-Memory Data Management for Transactional AND Query Processing

Traditionally, business applications have separated their data into an OLTP data store for high throughput transaction processing and a data warehouse for complex query processing. This separation bears severe maintenance and data consistency disadvantages. Two emerging hardware trends allow the consolidation of the two disparate workloads onto the same database state on one system: the increas...

متن کامل

HyPer: HYbrid OLTP&OLAP High PERformance Database System

The two areas of online transaction processing (OLTP) and online analytical processing (OLAP) present different challenges for database architectures. Currently, customers 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 h...

متن کامل

ScyPer: A Hybrid OLTP&OLAP Distributed Main Memory Database System for Scalable Real-Time Analytics

ScyPer is an abbreviation for Scaled-out HyPer, a version of the HyPer main memory hybrid OLTP&OLAP database system that horizontally scales out on sharednothing commodity hardware. Our demo shows that ScyPer a) achieves a near-linear scale-out of OLAP query throughput with the number of active nodes, b) sustains a constant OLTP throughput, c) is resilient to node failures, and d) offers real-t...

متن کامل

HyDash: A Dashboard for Real-Time Business Intelligence based on the HyPer Main Memory Database System

Business Intelligence (BI) is a set of techniques that help improve business decision making. From a technical point of view, BI relies on a set of tools which includes performance dashboards: layered services that combine monitoring, analysis, and reporting. However, most dashboard solutions today are based on data warehouses which face a problem of data staleness—a circumstance caused by the ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:
  • PVLDB

دوره 4  شماره 

صفحات  -

تاریخ انتشار 2011