1. Daniel Abadi Yale University

2. * The Big Data phenomenon is the best thing that could have happened to the database community * Despite other definitions related to ‘3 Vs’ --- Big Data means BIG Data * Which means we need scalable database systems * Still two main components of Big Data * Performing data analysis at scale * Performing requests on data at scale

3. * Database community has won the battle * Some thought that MapReduce might replace traditional database technology as the primary means to perform analysis at scale * Just about every MapReduce vendor has abandoned this goal * Hadapt, Impala, Tez, and several others are in a race to see who can add the most traditional database execution technology to Hadoop fastest * Everyone is going in the direction of cost-based optimizers, traditional database operators, and push-based query execution

4. * The database community is losing the battle * NoSQL systems still have very little traditional database technology inside (despite adding SQL interfaces) * No race to add DB technology --- why? * Don’t blame CAP --- CAP is only relevant when there’s a network partition * We never figured out how to do ACID and active replication at scale * Many new proposals make simplifying assumptions in order to handle scale * It’s been 30 years ---- why can’t we build a distributed database that can handle distributed transactions over actively replicated data at scale?