Main-memory scan sharing for multi-core CPUs
Proceedings of the VLDB Endowment
Row-wise parallel predicate evaluation
Proceedings of the VLDB Endowment
Brighthouse: an analytic data warehouse for ad-hoc queries
Proceedings of the VLDB Endowment
A common database approach for OLTP and OLAP using an in-memory column database
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
A scalable, predictable join operator for highly concurrent data warehouses
Proceedings of the VLDB Endowment
Predictable performance for unpredictable workloads
Proceedings of the VLDB Endowment
Variance aware optimization of parameterized queries
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Fast integer compression using SIMD instructions
Proceedings of the Sixth International Workshop on Data Management on New Hardware
Speeding up queries in column stores: a case for compression
DaWaK'10 Proceedings of the 12th international conference on Data warehousing and knowledge discovery
Predictable performance and high query concurrency for data analytics
The VLDB Journal — The International Journal on Very Large Data Bases
Online reorganization in read optimized MMDBS
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
LinearDB: a relational approach to make data warehouse scale like MapReduce
DASFAA'11 Proceedings of the 16th international conference on Database systems for advanced applications: Part II
Efficiently compiling efficient query plans for modern hardware
Proceedings of the VLDB Endowment
SharedDB: killing one thousand queries with one stone
Proceedings of the VLDB Endowment
Synopses for Massive Data: Samples, Histograms, Wavelets, Sketches
Foundations and Trends in Databases
Compacting transactional data in hybrid OLTP&OLAP databases
Proceedings of the VLDB Endowment
A storage advisor for hybrid-store databases
Proceedings of the VLDB Endowment
Overcoming the scalability limitations of parallel star schema data warehouses
ICA3PP'12 Proceedings of the 12th international conference on Algorithms and Architectures for Parallel Processing - Volume Part I
Providing timely results with an elastic parallel DW
ISMIS'12 Proceedings of the 20th international conference on Foundations of Intelligent Systems
Near real-time analytics with IBM DB2 analytics accelerator
Proceedings of the 16th International Conference on Extending Database Technology
BitWeaving: fast scans for main memory data processing
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
Data management systems on GPUs: promises and challenges
Proceedings of the 25th International Conference on Scientific and Statistical Database Management
DB2 with BLU acceleration: so much more than just a column store
Proceedings of the VLDB Endowment
Next generation data analytics at IBM research
Proceedings of the VLDB Endowment
Design and evaluation of storage organizations for read-optimized main memory databases
Proceedings of the VLDB Endowment
A comparison of knives for bread slicing
Proceedings of the VLDB Endowment
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Query performance in current systems depends significantly on tuning: how well the query matches the available indexes, materialized views etc. Even in a well tuned system, there are always some queries that take much longer than others. This frustrates users who increasingly want consistent response times to ad hoc queries. We argue that query processors should instead aim for constant response times for all queries, with no assumption about tuning. We present Blink, our first attempt at this goal, that runs every query as a table scan over a fully denormalized database, with hash group-by done along the way. To make this scan efficient, Blink uses a novel compression scheme that horizontally partitions tuples by frequency, thereby compressing skewed data almost down to entropy, even while producing long runs of fixed-length, easily-parseable values. We also present a scheme for evaluating a conjunction of range and equality predicates in SIMD fashion over compressed tuples, and different schemes for efficient hash-based aggregation within the L2 cache. A experimental study with a suite of arbitrary single block SQL queries over a TPCH-like schema suggests that constant-time queries can be efficient.