Jens Krueger

TL;DR: In this article, a relational database management system component and a column-oriented data processing component are combined to generate up-to-date reports without the need for extraction, translation and loading procedures.

TL;DR: This work presents an optimized merge process reducing the merge overhead of current systems by a factor of 30 and enables compressed in-memory column stores to handle the transactional update rate required by enterprise applications, while keeping properties of read-optimized databases for analytic-style queries.

TL;DR: In this paper, the authors describe a computer system for both online transaction processing and online analytical processing, comprising of a processor coupled to a database, the database comprising the database, a main store (116) for storing records, a differential buffer (114) for receiving and buffering added or deleted or modified records, and a cache store (112) for caching a result of a query against the schema; and the cache controller being configured for: storing the result of the query in the cache store; receiving an analytical request; and determining, in response to the received request, an

TL;DR: This paper proposes to use an additional write-optimized buffer to maintain the delta that in conjunction with the compressed main store represents the current state of the data, and uses the buffer as an intermediate storage for several modifications which are then populated as a bulk in a merge operation.

TL;DR: This paper analyzes typical operations in the area of multi-tenant databases and proposes an architecture for a multi-Tenant storage engine capable to overcome the problems of typical relational databases in this area.