geo-replication

  • Reading Group. UniStore: A fault-tolerant marriage of causal and strong consistency

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    For the 80th paper in the reading group, we picked “UniStore: A fault-tolerant marriage of causal and strong consistency” by Manuel Bravo, Alexey Gotsman, Borja de Régil, and Hengfeng Wei. This ATC’21 paper adapts the Partial Order-Restrictions consistency (PoR) into a transactional model. UniStore uses PoR to reduce coordination efforts and execute as many transactions…

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  • Reading Group. Fault-Tolerant Replication with Pull-Based Consensus in MongoDB

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    In the last reading group meeting, we discussed MongoDB‘s replication protocol, as described in the “Fault-Tolerant Replication with Pull-Based Consensus in MongoDB” NSDI’21 paper. Our reading group has a few regular members from MongoDB, and this time around, Siyuan Zhou, one of the paper authors, attended the discussion, so we had a perfect opportunity to…

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  • Reading Group. Near-Optimal Latency Versus Cost Tradeoffs in Geo-Distributed Storage

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    Short Summary Yesterday we discussed Pando, a geo-replication system achieving near-optimal latency-cost tradeoff in storage systems. Pando uses large Flexible Paxos deployments and erasure coding to do its magic. Pando relies on having many storage sites to locate sites closer to users. It then uses Flexible Paxos to optimize read and write quorums to have…

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  • Keep The Data Where You Use It

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    As trivial as it sounds, but keeping the data close to where it is consumed can drastically improve the performance of the large globe-spanning cloud applications, such as social networks, ecommerce and IoT. These applications rely on some database systems to make sure that all the data can be accessed quickly. The de facto method…

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  • One Page Summary: “PaxosStore: High-availability Storage Made Practical in WeChat”

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    PaxosStore paper, published in VLDB 2017, describes the large scale, multi-datacenter storage system used in WeChat. As the name may suggest, it uses Paxos to provide storage consistency. The system claims to provide storage for many components of the WeChat application, with 1.5TB of traffic per day and tens of thousands of queries per second…

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