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DBMS > Citus vs. Google BigQuery vs. Microsoft Access vs. Sphinx

System Properties Comparison Citus vs. Google BigQuery vs. Microsoft Access vs. Sphinx

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Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonGoogle BigQuery  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLLarge 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.)Open source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSRelational DBMSRelational DBMSSearch engine
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.13
Rank#117  Overall
#56  Relational DBMS
Score52.67
Rank#19  Overall
#13  Relational DBMS
Score93.76
Rank#12  Overall
#8  Relational DBMS
Score5.97
Rank#56  Overall
#5  Search engines
Websitewww.citusdata.comcloud.google.com/­bigquerywww.microsoft.com/­en-us/­microsoft-365/­accesssphinxsearch.com
Technical documentationdocs.citusdata.comcloud.google.com/­bigquery/­docsdeveloper.microsoft.com/­en-us/­accesssphinxsearch.com/­docs
DeveloperGoogleMicrosoftSphinx Technologies Inc.
Initial release2010201019922001
Current release8.1, December 20181902 (16.0.11328.20222), March 20193.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availablecommercialcommercial infoBundled with Microsoft OfficeOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC++C++
Server operating systemsLinuxhostedWindows infoNot a real database server, but making use of DLLsFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesno
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.yes infospecific XML type available, but no XML query functionalityno
Secondary indexesyesnoyesyes infofull-text index on all search fields
SQL infoSupport of SQLyes infostandard, with numerous extensionsyesyes infobut not compliant to any SQL standardSQL-like query language (SphinxQL)
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
RESTful HTTP/JSON APIADO.NET
DAO
ODBC
OLE DB
Proprietary protocol
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.user defined functions infoin JavaScriptyes infosince Access 2010 using the ACE-engineno
Triggersyesnoyes infosince Access 2010 using the ACE-engineno
Partitioning methods infoMethods for storing different data on different nodesShardingnonenoneSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno infoSince BigQuery is designed for querying dataACID infobut no files for transaction loggingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infobut no files for transaction loggingyes 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.nono
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess 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 2003no

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More resources
CitusGoogle BigQueryMicrosoft AccessSphinx
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