Abstract
Append/Log-based Storage and Multi-Version Database Management Systems (MV-DBMS) are gaining significant importance on new storage hardware technologies such as Flash and Non-Volatile Memories. Any modification of a data item in a MV-DBMS results in the creation of a new version. Traditional implementations, physically stamp old versions as invalidated, causing in-place updates resulting in random writes and ultimately in mixed loads, all of which are suboptimal for new storage technologies. Log-/Append-based Storage Managers (LbSM) insert new or modified data at the logical end of log-organised storage, converting in-place updates into small sequential appends. We claim that the combination of multi-versioning and append storage effectively addresses the characteristics of modern storage technologies.
We explore to what extent multi-versioning approaches such as Snapshot Isolation (SI) can benefit from Append-Based storage, and how a Flash-optimised approach called SIAS (Snapshot Isolation Append Storage) can improve performance. While traditional LbSM use coarse-grain page append granularity, SIAS performs appends in tuple-version granularity and manages versions as simply linked lists, thus avoiding in-place invalidations.
Our experimental results instrumenting a SSD with TPC-C generated OLTP load patterns show that: a) traditional LbSM approaches are up to 73% faster than their in-place update counterparts; b) SIAS tuple-version granularity append is up to 2.99x faster (IOPS and runtime) than in-place update storage managers; c) SIAS reduces the write overhead up to 52 times; d) in SIAS using exclusive append regions per relation is up to 5% faster than using one append region for all relations; e) SIAS I/O performance scales with growing parallelism, whereas traditional approaches reach early saturation.
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Gottstein, R., Petrov, I., Buchmann, A. (2013). Append Storage in Multi-Version Databases on Flash. In: Gottlob, G., Grasso, G., Olteanu, D., Schallhart, C. (eds) Big Data. BNCOD 2013. Lecture Notes in Computer Science, vol 7968. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39467-6_9
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