Quickly generating billion-record synthetic databases
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
Efficient locking for concurrent operations on B-trees
ACM Transactions on Database Systems (TODS)
Replicated indexes for distributed data
DIS '96 Proceedings of the fourth international conference on on Parallel and distributed information systems
Scalable, Efficient Range Queries for Grid Information Services
P2P '02 Proceedings of the Second International Conference on Peer-to-Peer Computing
A Peer-to-peer Framework for Caching Range Queries
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
Load balancing and locality in range-queriable data structures
Proceedings of the twenty-third annual ACM symposium on Principles of distributed computing
Brief announcement: prefix hash tree
Proceedings of the twenty-third annual ACM symposium on Principles of distributed computing
One torus to rule them all: multi-dimensional queries in P2P systems
Proceedings of the 7th International Workshop on the Web and Databases: colocated with ACM SIGMOD/PODS 2004
BATON: a balanced tree structure for peer-to-peer networks
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Structured Overlay without Consistent Hashing: Empirical Results
CCGRID '06 Proceedings of the Sixth IEEE International Symposium on Cluster Computing and the Grid
Dynamo: amazon's highly available key-value store
Proceedings of twenty-first ACM SIGOPS symposium on Operating systems principles
Online balancing of range-partitioned data with applications to peer-to-peer systems
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Range queries on structured overlay networks
Computer Communications
Bigtable: A Distributed Storage System for Structured Data
ACM Transactions on Computer Systems (TOCS)
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
A practical scalable distributed B-tree
Proceedings of the VLDB Endowment
PNUTS: Yahoo!'s hosted data serving platform
Proceedings of the VLDB Endowment
A comparison of approaches to large-scale data analysis
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Asynchronous view maintenance for VLSD databases
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
How is the weather tomorrow?: towards a benchmark for the cloud
Proceedings of the Second International Workshop on Testing Database Systems
HadoopDB: an architectural hybrid of MapReduce and DBMS technologies for analytical workloads
Proceedings of the VLDB Endowment
Benchmarking cloud serving systems with YCSB
Proceedings of the 1st ACM symposium on Cloud computing
Benchmarking cloud-based data management systems
CloudDB '10 Proceedings of the second international workshop on Cloud data management
Towards elastic transactional cloud storage with range query support
Proceedings of the VLDB Endowment
Scalable SQL and NoSQL data stores
ACM SIGMOD Record
Replication, load balancing and efficient range query processing in DHTs
EDBT'06 Proceedings of the 10th international conference on Advances in Database Technology
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Recently there has been a considerable increase in the number of different Key-Value stores, for supporting data storage and applications on the cloud environment. While all these solutions try to offer highly available and scalable services on the cloud, they are significantly different with each other in terms of the architecture and types of the applications, they try to support. Considering three widely-used such systems: Cassandra, HBase and Voldemort; in this paper we compare them in terms of their support for different types of query workloads. We are mainly focused on the range queries. Unlike HBase and Cassandra that have built-in support for range queries, Voldemort does not support this type of queries via its available API. For this matter, practical techniques are presented on top of Voldemort to support range queries. Our performance evaluation is based on mixed query workloads, in the sense that they contain a combination of short and long range queries, beside other types of typical queries on key-value stores such as lookup and update. We show that there are trade-offs in the performance of the selected system and scheme, and the types of the query workloads that can be processed efficiently.