TiQuE: Improving the Transactional Performance of Analytical Systems for True Hybrid Workloads

Author:

Faria Nuno1,Pereira José1,Alonso Ana Nunes1,Vilaça Ricardo1,Koning Yunus2,Nes Niels3

Affiliation:

1. INESCTEC and University of Minho, Braga, Portugal

2. MonetDB Solutions, Amsterdam, The Netherlands

3. MonetDB Solutions and CWI Amsterdam, The Netherlands

Abstract

Transactions have been a key issue in database management for a long time and there are a plethora of architectures and algorithms to support and implement them. The current state-of-the-art is focused on storage management and is tightly coupled with its design, leading, for instance, to the need for completely new engines to support new features such as Hybrid Transactional Analytical Processing (HTAP). We address this challenge with a proposal to implement transactional logic in a query language such as SQL. This means that our approach can be layered on existing analytical systems but that the retrieval of a transactional snapshot and the validation of update transactions runs in the server and can take advantage of advanced query execution capabilities of an optimizing query engine. We demonstrate our proposal, TiQuE, on MonetDB and obtain an average 500x improvement in transactional throughput while retaining good performance on analytical queries, making it competitive with the state-of-the-art HTAP systems.

Publisher

Association for Computing Machinery (ACM)

Subject

General Earth and Planetary Sciences,Water Science and Technology,Geography, Planning and Development

Reference111 articles.

1. 2021. Snapshot Isolation in SQL Server. https://learn.microsoft.com/en-us/dotnet/framework/data/adonet/sql/snapshot-isolation-in-sql-server. 2021. Snapshot Isolation in SQL Server. https://learn.microsoft.com/en-us/dotnet/framework/data/adonet/sql/snapshot-isolation-in-sql-server.

2. 2022. Elle - Black-box transactional safety checker based on cycle detection. https://github.com/jepsen-io/elle. 2022. Elle - Black-box transactional safety checker based on cycle detection. https://github.com/jepsen-io/elle.

3. 2022. Galera Cluster. https://galeracluster.com/. 2022. Galera Cluster. https://galeracluster.com/.

4. 2022. Hive Transactions. https://hbase.apache.org/acid-semantics.html. 2022. Hive Transactions. https://hbase.apache.org/acid-semantics.html.

5. 2022. IBM Db2 Database. https://www.ibm.com/products/db2-database. 2022. IBM Db2 Database. https://www.ibm.com/products/db2-database.

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