C-Store: A Column-oriented DBMS

By M. Stonebraker, Daniel J. Abadi, A. Batkin, Xuedong Chen, Mitch Cherniack, Miguel Ferreira, Edmond Lau, Amerson Lin, Samuel Madden, E. O'Neil and 4 more. Very Large Data Bases Conference, 2005

1,312 citations recorded by the source corpus.

This paper presents the design of a read-optimized relational DBMS that contrasts sharply with most current systems, which are write-optimized. Among the many differences in its design are: storage of data by column rather than by row, careful coding and packing of objects into storage including main memory during query processing, storing an overlapping collection of column-oriented projections, rather than the current fare of tables and indexes, a non-traditional implementation of transactions which includes high availability and snapshot isolation for read-only transactions, and the extensive use of bitmap indexes to complement B-tree structures.We present preliminary performance data on a subset of TPC-H and show that the system we are building, C-Store, is substantially faster than popular commercial products. Hence, the architecture looks very encouraging.

Subfields: Computer Networks and Communications

View Paper: https://www.semanticscholar.org/paper/88087bd6b61eeb44148041ab4d1939b65f89e73b

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Citations in the corpus

Cache locality is not enough: High-Performance Nearest Neighbor Search with Product Quantization Fast Scan (2015, neutral): “Compression schemes, either generic [23, 12, 3, 25] or speciﬁc (e.g., SAX for time series [18]), have been widely adopted in database systems.”
Database Cracking (2007, background): “The recently proposed system C-Store [14] is related to cracking in many interesting ways.”
Shark: SQL and rich analytics at scale (2012, positive): “Similar to more traditional database systems [27], Shark implements CPU-efﬁcient compression schemes such as dictionary encoding, run-length encoding, and bit packing.”
Hexastore: sextuple indexing for semantic web data management (2008, methodology): “In [5], this approach is coupled with a column-oriented DBMS [14] [15] [42] (i.e., a DBMS designed especially for the vertically partitioned case, as opposed to a row-oriented DBMS, gaining benefits of compressibility [4] and performance [7]).”
SW-Store: a vertically partitioned DBMS for Semantic Web data management (2009, methodology): “Although the column-store idea has been around for some time [11], there has been a recent revival in column-oriented research and commercial products [15,16,33,45].”
H-store: a high-performance, distributed main memory transaction processing system (2008, background): “Previous literature introduced the concept of k-safety in distributed database systems, where k is defined as the number of node failures a database is designed to tolerate [7].”
Benchmarking cloud serving systems with YCSB (2010, neutral): “Pavlo et al [26] have benchmarked cloud systems like Hadoop against more traditional relational systems and relational column stores like Vertica/C-Store [32].”
When things matter: A survey on data-centric internet of things (2016, methodology): “C-Store, a column-store architecture that supports the standard relational logical data model, has been designed by Stonebraker et al. (2005).”
Relational joins on graphics processors (2008, methodology): “All join algorithms operate on memory-resident data organized in the column-based model [10][35].”
Incremental Detection of Inconsistencies in Distributed Data (2014, methodology): “In some applications ( e.g., [29]) one wants to partition D into ( D 1 , . . . , D n ) [25] such that where X i is a set of attributes of R on which D is projected, including a key attribute of R .”
Overview of sciDB: large scale array storage, processing and analysis (2010, background): “First, in common with the so-called column-store storage managers[1, 7] , we vertically partition the data in our arrays.”
MAD Skills: New Analysis Practices for Big Data (2009, background): “In a recent version Greenplum also adds “columnstore” partitioning of append-only tables, akin to ideas in the literature [20].”
Bigtable: A Distributed Storage System for Structured Data (2008, background): “…bene.ts observed for other systems that organize data on disk using column-based ratherthan row-based storage,includingC-Store[Abadi et al. 2006; Stonebraker et al. 2005] and commercial products such as Sybase IQ [French1995; sybase.com],SenSage[sensage.com],KDB+[kx.com], andthe ColumnBM…”
HadoopDB: An Architectural Hybrid of MapReduce and DBMS Technologies for Analytical Workloads (2009, methodology): “Vertica is a relatively new parallel database system (founded in 2005) [3] based on the C-Store research project [24].”
RCFile: A fast and space-efficient data placement structure in MapReduce-based warehouse systems (2011, background): “[10] M. Stonebraker, D. J. Abadi, A. Batkin, X. Chen, M. Cherniack, M. Ferreira, E. Lau, A. Lin, S. Madden, E. J. O’Neil, P. E. O’Neil, A. Rasin, N. Tran, and S. B. Zdonik, “C-store: A column-oriented dbms,” in VLDB, 2005, pp. 553–564.”