2015
DOI: 10.14778/2824032.2824065
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Schema-agnostic indexing with Azure DocumentDB

Abstract: Azure DocumentDB is Microsoft's multi-tenant distributed database service for managing JSON documents at Internet scale. DocumentDB is now generally available to Azure developers. In this paper, we describe the DocumentDB indexing subsystem. DocumentDB indexing enables automatic indexing of documents without requiring a schema or secondary indices. Uniquely, DocumentDB provides real-time consistent queries in the face of very high rates of document updates. As a multi-tenant service, DocumentDB is designed to … Show more

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Cited by 32 publications
(15 citation statements)
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“…A MongoDB [ 67 ] distributed database has been used for persistent data storage. We have used MongoDB Atlas [ 68 ] and Azure DocumentDB [ 69 ]. While both of them had a very good response time (less than 1 ms), Document DB proved to be very expensive as it is charged per request.…”
Section: Discussion and Resultsmentioning
confidence: 99%
“…A MongoDB [ 67 ] distributed database has been used for persistent data storage. We have used MongoDB Atlas [ 68 ] and Azure DocumentDB [ 69 ]. While both of them had a very good response time (less than 1 ms), Document DB proved to be very expensive as it is charged per request.…”
Section: Discussion and Resultsmentioning
confidence: 99%
“…We begin with a review of existing CAS indexes [8,20,23,25,39]. IndexFabric [8] prioritizes the structure of the data over its values.…”
Section: Related Workmentioning
confidence: 99%
“…As real-world BOMs grow to tens of millions of nodes [11], we need dedicated CAS access methods to support the efficient processing of CAS queries. Existing CAS indexes often lead to large intermediate results, since they either build separate indexes for, respectively, content and structure [25] or prioritize one dimension over the other (i.e., content over structure or vice versa) [2,8,39]. We propose a well-balanced integration of paths and values in a single index that provides robust performance for CAS queries, meaning that the index prioritizes neither paths nor values.…”
Section: Introductionmentioning
confidence: 99%
“…RAMCloud [41], FaRM-KV [14], HBase [20], Cassandra [28], LevelDB [23], and RocksDB [16]) all of which show good get/put performance, but have difficulties to process scans with a competitive performance. Another interesting line of related work are document stores, like DocumentDB [42] or MongoDB [32]. Like Cassandra, they offer some scans with secondary indexes, specifically tuned to the document-related use-cases.…”
Section: Related Workmentioning
confidence: 99%