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DBMS > Amazon DocumentDB vs. Google BigQuery vs. Rockset vs. Sphinx

System Properties Comparison Amazon DocumentDB vs. Google BigQuery vs. Rockset vs. Sphinx

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonGoogle BigQuery  Xexclude from comparisonRockset  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceLarge scale data warehouse service with append-only tablesA scalable, reliable search and analytics service in the cloud, built on RocksDBOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeRelational DBMSDocument storeSearch engine
Secondary database modelsRelational DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score60.38
Rank#19  Overall
#13  Relational DBMS
Score0.79
Rank#211  Overall
#35  Document stores
Score5.98
Rank#56  Overall
#5  Search engines
Websiteaws.amazon.com/­documentdbcloud.google.com/­bigqueryrockset.comsphinxsearch.com
Technical documentationaws.amazon.com/­documentdb/­resourcescloud.google.com/­bigquery/­docsdocs.rockset.comsphinxsearch.com/­docs
DeveloperGoogleRocksetSphinx Technologies Inc.
Initial release2019201020192001
Current release3.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++
Server operating systemshostedhostedhostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesdynamic typingno
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonono infoingestion from XML files supported
Secondary indexesyesnoall fields are automatically indexedyes infofull-text index on all search fields
SQL infoSupport of SQLnoyesRead-only SQL queries, including JOINsSQL-like query language (SphinxQL)
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)RESTful HTTP/JSON APIHTTP RESTProprietary protocol
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
Go
Java
JavaScript (Node.js)
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnouser defined functions infoin JavaScriptnono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesnonenoneAutomatic shardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsno infoSince BigQuery is designed for querying datanono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlAccess rights for users and rolesAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)Access rights for users and organizations can be defined via Rockset consoleno

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More resources
Amazon DocumentDBGoogle BigQueryRocksetSphinx
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