ACIDRain: concurrency-related attacks on database backed web applications

ACIDRain: Concurrency-related attacks on database-backed web applications Warszawski & Bailis, SIGMOD'17 Welcome back to a new term of The Morning Paper. To kick things off, we have 'ACID Rain' - a terrific paper from SIGMOD'17 that pulls together a number of threads we've studied previously: transaction processing, anomalies, and security. What ACIDRain demonstrates is that … Continue reading ACIDRain: concurrency-related attacks on database backed web applications

Omid reloaded: scalable and highly-available transaction processing

Omid, reloaded: scalable and highly-available transaction processing Shacham et al., FAST '17 Omid is a transaction processing service powering web-scale production systems at Yahoo that digest billions of events per day and push them into a real-time index. It's also been open-sourced and is currently incubating at Apache as the Apache Omid project. What's interesting … Continue reading Omid reloaded: scalable and highly-available transaction processing

SnappyData: A unified cluster for streaming, transactions, and interactive analytics

SnappyData: A unified cluster for streaming, transactions, and interactive analytics Mozafari et al., CIDR 2017 Update: fixed broken paper link, thanks Zteve. On Monday we looked at Weld which showed how to combine disparate data processing and analytic frameworks using a common underlying IR. Yesterday we looked at Peloton that adapts to mixed OLTP and … Continue reading SnappyData: A unified cluster for streaming, transactions, and interactive analytics

Adaptive logging: optimizing logging and recovery costs in distributed in-memory databases

Adaptive Logging: Optimizing logging and recovery costs in distributed In-memory databases Yao et al., SIGMOD 2016 This is a paper about the trade-offs between transaction throughput and database recovery time. Intuitively for example, you can do a little more work on each transaction (lowering throughput) in order to reduce the time it takes to recover … Continue reading Adaptive logging: optimizing logging and recovery costs in distributed in-memory databases

FaSST: Fast, scalable and simple distributed transactions with two-sided (RDMA) datagram RPCs

FaSST: Fast, scalable and simple distributed transactions with two-sided (RDMA) datagram rpcs Kalia et al., OSDI 2016 Back in January I wrote a short piece entitled ‘All change please’ looking at some of the hardware changes making their way to our datacenters and the implications. One of those changes is super-fast networking (as exploited by … Continue reading FaSST: Fast, scalable and simple distributed transactions with two-sided (RDMA) datagram RPCs

Diamond: Automating data management and storage for wide-area, reactive applications

Diamond: Automating data management and storage for wide-area, reactive applications Zhang et al., OSDI 2016 Diamond tackles the end-to-end problem of building reactive applications, defined here as those that update end-user visible state without requiring any explicit user action: … today’s popular applications are reactive: they provide users with the illusion of continuous synchronization across … Continue reading Diamond: Automating data management and storage for wide-area, reactive applications

The SNOW theorem and latency-optimal read-only transactions

The SNOW theorem and latency-optimal read-only transactions Lu et al., OSDI 2016 Consider a read-only workload (as in 100%). You can make that really fast - never any need to coordinate, never any need to invalidate any cached values… Now consider a write-only workload - you can make that even faster, if no-one’s ever going … Continue reading The SNOW theorem and latency-optimal read-only transactions