{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,8]],"date-time":"2026-04-08T09:01:52Z","timestamp":1775638912856,"version":"3.50.1"},"reference-count":34,"publisher":"Association for Computing Machinery (ACM)","issue":"14","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2013,9]]},"abstract":"<jats:p>The traditional wisdom for building disk-based relational database management systems (DBMS) is to organize data in heavily-encoded blocks stored on disk, with a main memory block cache. In order to improve performance given high disk latency, these systems use a multi-threaded architecture with dynamic record-level locking that allows multiple transactions to access the database at the same time. Previous research has shown that this results in substantial overhead for on-line transaction processing (OLTP) applications [15].<\/jats:p>\n          <jats:p>The next generation DBMSs seek to overcome these limitations with architecture based on main memory resident data. To overcome the restriction that all data fit in main memory, we propose a new technique, called anti-caching, where cold data is moved to disk in a transactionally-safe manner as the database grows in size. Because data initially resides in memory, an anti-caching architecture reverses the traditional storage hierarchy of disk-based systems. Main memory is now the primary storage device.<\/jats:p>\n          <jats:p>We implemented a prototype of our anti-caching proposal in a high-performance, main memory OLTP DBMS and performed a series of experiments across a range of database sizes, workload skews, and read\/write mixes. We compared its performance with an open-source, disk-based DBMS optionally fronted by a distributed main memory cache. Our results show that for higher skewed workloads the anti-caching architecture has a performance advantage over either of the other architectures tested of up to 9\u00d7 for a data size 8\u00d7 larger than memory.<\/jats:p>","DOI":"10.14778\/2556549.2556575","type":"journal-article","created":{"date-parts":[[2014,6,24]],"date-time":"2014-06-24T12:17:57Z","timestamp":1403612277000},"page":"1942-1953","source":"Crossref","is-referenced-by-count":96,"title":["Anti-caching"],"prefix":"10.14778","volume":"6","author":[{"given":"Justin","family":"DeBrabant","sequence":"first","affiliation":[{"name":"Brown University"}]},{"given":"Andrew","family":"Pavlo","sequence":"additional","affiliation":[{"name":"Brown University"}]},{"given":"Stephen","family":"Tu","sequence":"additional","affiliation":[{"name":"MIT CSAIL"}]},{"given":"Michael","family":"Stonebraker","sequence":"additional","affiliation":[{"name":"MIT CSAIL"}]},{"given":"Stan","family":"Zdonik","sequence":"additional","affiliation":[{"name":"Brown University"}]}],"member":"320","published-online":{"date-parts":[[2013,9]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"eXtremeDB. http:\/\/www.mcobject.com."},{"key":"e_1_2_1_2_1","unstructured":"H-Store. http:\/\/hstore.cs.brown.edu."},{"key":"e_1_2_1_3_1","unstructured":"MemSQL. http:\/\/www.memsql.com."},{"key":"e_1_2_1_4_1","unstructured":"VoltDB. http:\/\/www.voltdb.com."},{"key":"e_1_2_1_5_1","volume-title":"February","author":"TimesTen Products Oracle","year":"2007","unstructured":"Oracle TimesTen Products and Technologies. 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