EAGER: Scaling the Preprocessor and Making it More Intelligent in Deterministic Database Systems

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This research aims to bridge the gap between the current reality and the potential for database system deployments on large clusters of servers in a data center or large numbers of virtual machines in the cloud. There does not exist a scalable, elastic, ACID-compliant database system implementation today. In general, applications that require elastic scalability are forced to program around the lack of ACID guarantees of the database system, and many applications are too complicated to be rewritten to work around these issues. The goal of this project is to overcome these issues using the following approaches: (1) Implementing a database system using an innovative deterministic architecture that guarantees that nondeterministic processing events will not affect database state, (2) Leveraging this new architecture to avoid "commit protocols" for distributed transactions in a cluster, (3) Designing a scalable preprocessor for the deterministic database that collects, analyzes, and dispatches transactions to the database cluster in order to further improve scalability, and (4) Developing a new lazy transaction evaluation approach in order to spread out load and avoid damaging effects of database load spikes. Overall, this research enables thousands of applications written for many different use-cases (such as e-commerce, telecommunications, and online auctions) to achieve scalability "for free" without having to rewrite the application code. This research involves both Ph.D. students and undergraduates, with significant outreach efforts to encourage undergraduates to get involved in research. Open source code, publications, and technical reports from this research will be disseminated via the project web site http://db.cs.yale.edu/determinism/.