An architecture for a business and information system
IBM Systems Journal
ACM Transactions on Database Systems (TODS)
IBM Systems Journal
Item-based collaborative filtering recommendation algorithms
Proceedings of the 10th international conference on World Wide Web
Building the Data Warehouse,3rd Edition
Building the Data Warehouse,3rd Edition
Amazon.com Recommendations: Item-to-Item Collaborative Filtering
IEEE Internet Computing
User's Guide to Websphere Extreme Scale
User's Guide to Websphere Extreme Scale
Benchmarking cloud serving systems with YCSB
Proceedings of the 1st ACM symposium on Cloud computing
The YouTube video recommendation system
Proceedings of the fourth ACM conference on Recommender systems
Large-scale incremental processing using distributed transactions and notifications
OSDI'10 Proceedings of the 9th USENIX conference on Operating systems design and implementation
10 rules for scalable performance in 'simple operation' datastores
Communications of the ACM
Communications of the ACM
An overview of business intelligence technology
Communications of the ACM
High performance database logging using storage class memory
ICDE '11 Proceedings of the 2011 IEEE 27th International Conference on Data Engineering
Fast crash recovery in RAMCloud
SOSP '11 Proceedings of the Twenty-Third ACM Symposium on Operating Systems Principles
Memcached Design on High Performance RDMA Capable Interconnects
ICPP '11 Proceedings of the 2011 International Conference on Parallel Processing
NoSQL databases: a step to database scalability in web environment
Proceedings of the 13th International Conference on Information Integration and Web-based Applications and Services
Web-scale user modeling for targeting
Proceedings of the 21st international conference companion on World Wide Web
bLSM: a general purpose log structured merge tree
SIGMOD '12 Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data
Proceedings of the 15th International Conference on Extending Database Technology
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Emerging transactional workloads from Internet and mobile commerce require low-latency, massive-scale, and integrated data analytics to enhance user experience and to improve up-selling opportunities. These analytics require new application platforms that must be able to absorb large volumes of data, provide low-latency access to the data, and cache data objects to improve access times in distributed environments. This paper reports on recent technologies built at IBM Research to address challenges in data access latency, data ingestion, and caching in the exemplary context of an online product recommendation application. We describe three technologies related to the issues and optimizations of key-value data object store and access. First, we describe the architecture of a global secondary index to greatly improve data access latency of Hadoop™ Database (HBase™), an open-source key-value distributed data store. Second, we present an in-memory write-ahead log feature on HBase that significantly improves write operations for high-volume data ingestion. Third, we detail an innovative distributed caching system that exploits low-latency interconnects to use hash maps of data keys on each server for local lookup, while data resides and are accessed across clustered systems. The distributed cache can achieve a 100-to 1,000-fold performance gain over many caching methods. These technologies together form some necessary building blocks for a next-generation data-centric middleware for integrated transaction and analytic workloads.