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DBMS > Google BigQuery vs. Microsoft Access vs. Riak KV vs. Sphinx

System Properties Comparison Google BigQuery vs. Microsoft Access vs. Riak KV vs. Sphinx

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Editorial information provided by DB-Engines
NameGoogle BigQuery  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonRiak KV  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionLarge scale data warehouse service with append-only tablesMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)Distributed, fault tolerant key-value storeOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSRelational DBMSKey-value store infowith links between data sets and object tags for the creation of secondary indexesSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score58.10
Rank#19  Overall
#13  Relational DBMS
Score101.16
Rank#11  Overall
#8  Relational DBMS
Score4.01
Rank#79  Overall
#9  Key-value stores
Score5.95
Rank#55  Overall
#5  Search engines
Websitecloud.google.com/­bigquerywww.microsoft.com/­en-us/­microsoft-365/­accesssphinxsearch.com
Technical documentationcloud.google.com/­bigquery/­docsdeveloper.microsoft.com/­en-us/­accesswww.tiot.jp/­riak-docs/­riak/­kv/­latestsphinxsearch.com/­docs
DeveloperGoogleMicrosoftOpenSource, formerly Basho TechnologiesSphinx Technologies Inc.
Initial release2010199220092001
Current release1902 (16.0.11328.20222), March 20193.2.0, December 20223.5.1, February 2023
License infoCommercial or Open Sourcecommercialcommercial infoBundled with Microsoft OfficeOpen Source infoApache version 2, commercial enterprise editionOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ErlangC++
Server operating systemshostedWindows infoNot a real database server, but making use of DLLsLinux
OS X
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnono
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.nono
Secondary indexesnoyesrestrictedyes infofull-text index on all search fields
SQL infoSupport of SQLyesyes infobut not compliant to any SQL standardnoSQL-like query language (SphinxQL)
APIs and other access methodsRESTful HTTP/JSON APIADO.NET
DAO
ODBC
OLE DB
HTTP API
Native Erlang Interface
Proprietary protocol
Supported programming languages.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresuser defined functions infoin JavaScriptyes infosince Access 2010 using the ACE-engineErlangno
Triggersnoyes infosince Access 2010 using the ACE-engineyes infopre-commit hooks and post-commit hooksno
Partitioning methods infoMethods for storing different data on different nodesnonenoneSharding infono "single point of failure"Sharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesnoneselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesno infolinks between data sets can be storedno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoSince BigQuery is designed for querying dataACID infobut no files for transaction loggingnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infobut no files for transaction loggingyesyes 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 privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)no infoa simple user-level security was built in till version Access 2003yes, using Riak Securityno

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Google BigQueryMicrosoft AccessRiak KVSphinx
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