Benchmarking Hybrid OLTP&OLAP Database Systems
نویسندگان
چکیده
Recently, the case has been made for operational or real-time Business Intelligence (BI). As the traditional separation into OLTP database and OLAP data warehouse obviously incurs severe latency disadvantages for operational BI, hybrid OLTP&OLAP database systems are being developed. The advent of the first generation of such hybrid OLTP&OLAP database systems requires means to characterize their performance. While there are standardized and widely used benchmarks addressing either OLTP or OLAP workloads, the lack of a hybrid benchmark led us to the definition of a new mixed workload benchmark, called TPC-CH. This benchmark bridges the gap between the existing single-workload suits: TPC-C for OLTP and TPC-H for OLAP. The newly proposed TPC-CH benchmark executes a mixed workload: A transactional workload based on the order entry processing of TPC-C and a corresponding TPC-H-equivalent OLAP query suite on this sales data base. As it is derived from these two most widely used TPC benchmarks our new TPC-CH benchmark produces results that are highly comparable to both, hybrid systems and classic single-workload systems. Thus, we are able to compare the performance of our own (and other) hybrid database system running both OLTP and OLAP workloads in parallel with the OLTP performance of dedicated transactional systems (e.g., VoltDB) and the OLAP performance of specialized OLAP databases (e.g., column stores such as MonetDB).
منابع مشابه
Normalization in a Mixed OLTP and OLAP Workload Scenario
The historically introduced separation of online analytical processing (OLAP) from online transaction processing (OLTP) is in question considering the current developments of databases. Columnoriented databases mainly used in the OLAP environment so far, with the addition of in-memory data storage are adapted to accommodate OLTP as well, thus paving the way for mixed OLTP and OLAP processing. T...
متن کاملHyPer: 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 کاملCompacting Transactional Data in Hybrid OLTP & OLAP Databases
Growing main memory sizes have facilitated database management systems that keep the entire database in main memory. The drastic performance improvements that came along with these in-memory systems have made it possible to reunite the two areas of online transaction processing (OLTP) and online analytical processing (OLAP): An emerging class of hybrid OLTP and OLAP database systems allows to p...
متن کاملHyPer-sonic Combined Transaction AND Query Processing
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 cha...
متن کاملTastes Great, Less Filling: Low-Impact OLAP MapReduce Queries on High-Performance OLTP Systems
The previous decade saw the rise of separate, dedicated database management systems (DBMS) for online transaction processing (OLTP) and online analytical processing (OLAP) workloads [3]. The former are focused on executing short-lived, small-footprint transactions with high throughput and strong consistency guarantees. OLAP DBMSs typically target longer running and more complex queries that exa...
متن کامل