Veritas: shared verifiable databases and tables in the cloud

Veritas: shared verifiable databases and tables in the cloud Allen et al., CIDR'19 Two (or more) parties want to transact based on the sharing of information (e.g. current offers). In order to have trust in the system and provide a foundation for resolving disputes, we’d like a tamperproof and immutable audit log of all shared … Continue reading Veritas: shared verifiable databases and tables in the cloud

The case for network-accelerated query processing

The case for network-accelerated query processing Lerner et al., CIDR'19 Datastores continue to advance on a number of fronts. Some of those that come to mind are adapting to faster networks (e.g. ‘FARM: Fast Remote Memory’) and persistent memory (see e.g. ‘Let’s talk about storage and recovery methods for non-volatile memory database systems’), deeply integrating … Continue reading The case for network-accelerated query processing

Programming paradigms for dummies: what every programmer should know

Programming paradigms for dummies: what every programmer should know Peter Van Roy, 2009 We’ll get back to CIDR’19 next week, but chasing the thread starting with the Data Continuum paper led me to this book chapter by Peter Van Roy mapping out the space of programming language designs. (Thanks to TuringTest for posting a reference … Continue reading Programming paradigms for dummies: what every programmer should know

The data calculator: data structure design and cost synthesis from first principles and learned cost models

The Data Calculator: data structure design and cost synthesis from first principles and learned cost models Idreos et al., SIGMOD'18 This paper preceded the work on data continuums that we looked at last time, and takes a more general look at interactive and semi-automated design of data structures. A data structure here is defined as … Continue reading The data calculator: data structure design and cost synthesis from first principles and learned cost models

Design continuums and the path toward self-designing key-value stores that know and learn

Design continuums and the path toward self-designing key-value stores that know and learn Idreos et al., CIDR'19 We’ve seen systems that help to select the best data structure from a pre-defined set of choices (e.g. ‘Darwinian data structure selection’), systems that synthesise data structure implementations given an abstract specification (‘Generalized data structure synthesis’), systems that … Continue reading Design continuums and the path toward self-designing key-value stores that know and learn

Towards a hands-free query optimizer through deep learning

Towards a hands-free query optimizer through deep learning Marcus & Papaemmanouil, CIDR'19 Where the SageDB paper stopped— at the exploration of learned models to assist in query optimisation— today’s paper choice picks up, looking exclusively at the potential to apply learning (in this case deep reinforcement learning) to build a better optimiser. Why reinforcement learning? … Continue reading Towards a hands-free query optimizer through deep learning