Weighted voting for replicated data
SOSP '79 Proceedings of the seventh ACM symposium on Operating systems principles
Bigtable: a distributed storage system for structured data
OSDI '06 Proceedings of the 7th USENIX Symposium on Operating Systems Design and Implementation - Volume 7
Sinfonia: a new paradigm for building scalable distributed systems
Proceedings of twenty-first ACM SIGOPS symposium on Operating systems principles
Dynamo: amazon's highly available key-value store
Proceedings of twenty-first ACM SIGOPS symposium on Operating systems principles
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
OLTP through the looking glass, and what we found there
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
PNUTS: Yahoo!'s hosted data serving platform
Proceedings of the VLDB Endowment
Benchmarking cloud serving systems with YCSB
Proceedings of the 1st ACM symposium on Cloud computing
G-Store: a scalable data store for transactional multi key access in the cloud
Proceedings of the 1st ACM symposium on Cloud computing
ElasTraS: an elastic transactional data store in the cloud
HotCloud'09 Proceedings of the 2009 conference on Hot topics in cloud computing
Large-scale incremental processing using distributed transactions and notifications
OSDI'10 Proceedings of the 9th USENIX conference on Operating systems design and implementation
Using Paxos to build a scalable, consistent, and highly available datastore
Proceedings of the VLDB Endowment
Database Replication
Proceedings of the VLDB Endowment
Adapting microsoft SQL server for cloud computing
ICDE '11 Proceedings of the 2011 IEEE 27th International Conference on Data Engineering
Transactional storage for geo-replicated systems
SOSP '11 Proceedings of the Twenty-Third ACM Symposium on Operating Systems Principles
Probabilistically bounded staleness for practical partial quorums
Proceedings of the VLDB Endowment
F1: the fault-tolerant distributed RDBMS supporting google's ad business
SIGMOD '12 Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data
Serializability, not serial: concurrency control and availability in multi-datacenter datastores
Proceedings of the VLDB Endowment
Elastic Scale-Out for Partition-Based Database Systems
ICDEW '12 Proceedings of the 2012 IEEE 28th International Conference on Data Engineering Workshops
Spanner: Google's globally-distributed database
OSDI'12 Proceedings of the 10th USENIX conference on Operating Systems Design and Implementation
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Many applications hosted on the cloud have sophisticated data management needs that are best served by a SQL-based relational DBMS. It is not difficult to run a DBMS in the cloud, and in many cases one DBMS instance is enough to support an application's workload. However, a DBMS running in the cloud (or even on a local server) still needs a way to persistently store its data and protect it against failures. One way to achieve this is to provide a scalable and reliable storage service that the DBMS can access over a network. This paper describes such a service, which we call DAX. DAX relies on multi-master replication and Dynamo-style flexible consistency, which enables it to run in multiple data centers and hence be disaster tolerant. Flexible consistency allows DAX to control the consistency level of each read or write operation, choosing between strong consistency at the cost of high latency or weak consistency with low latency. DAX makes this choice for each read or write operation by applying protocols that we designed based on the storage tier usage characteristics of database systems. With these protocols, DAX provides a storage service that can host multiple DBMS tenants, scaling with the number of tenants and the required storage capacity and bandwidth. DAX also provides high availability and disaster tolerance for the DBMS storage tier. Experiments using the TPC-C benchmark show that DAX provides up to a factor of 4 performance improvement over baseline solutions that do not exploit flexible consistency.