ASTral / JITDs

Active Students: Darshana Balakrishnan, Carl Nuessle, Nicholas Brown

Supported By: NSF Award #IIS-1617586

Recently, a swath of specialized data management systems has attempted to displace traditional relational databsaes, each sacrificing a measure of physical independence for the consequent performance gains. However, relying on an entire data management system built around a specific set of performance/capability tradeoffs requires making strong assumptions about (often unpredictable) workload expectations. ASTral does for specialized databse systems what self-describing data did for specialized schemas.  ASTral involves several sub-projects:

Just-In-Time Data Structures

ASTral is based on an idea called Just-in-time datastructures, where data structure manipulation and access logic are decoupled from the physical representation. A just-in-time data structure uses a set of simple semantic and structural building blocks both to emulate the behavior of existing data structures, and to dynamically create new data structures synthesized on-the-spot to match presented workloads.

(The ASTral project is being developed in collaboration with Luke Ziarek)



TreeToaster: Towards an IVM-Optimized Compiler
Benchmarking Pocket-Scale Databases
Fluid Data Structures
Just-in-Time Index Compilation
Not Your Father's Big Data
Pocket Data: The Need for TPC-MOBILE
Oliver Kennedy, Jerry Antony Ajay, Geoffrey Challen, Lukasz Ziarek
Just in Time Datastructures
Oliver Kennedy, Lukasz Ziarek
Laasie: Towards One-Size-Fits-All Database
Ankur Upadhyay
Monadic Logs for Collaborative Web Applications
Sumit Agarwal, Daniel Bellinger, Oliver Kennedy, Ankur Upadhyay, Lukasz Ziarek
$Bar_{QL}$: Collaborating Through Change
Oliver Kennedy, Lukasz Ziarek
$Bar_{QL}$: Collaborating through Change
Oliver Kennedy, Lukasz Ziarek

Other Material

This page last updated 2024-05-06 11:22:18 -0400