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DBMS > Google BigQuery vs. Microsoft Access vs. Quasardb vs. Stardog

System Properties Comparison Google BigQuery vs. Microsoft Access vs. Quasardb vs. Stardog

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Editorial information provided by DB-Engines
NameGoogle BigQuery  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonQuasardb  Xexclude from comparisonStardog  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, high-performance timeseries databaseEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelRelational DBMSRelational DBMSTime Series DBMSGraph DBMS
RDF store
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
Score0.21
Rank#322  Overall
#29  Time Series DBMS
Score2.07
Rank#122  Overall
#11  Graph DBMS
#6  RDF stores
Websitecloud.google.com/­bigquerywww.microsoft.com/­en-us/­microsoft-365/­accessquasar.aiwww.stardog.com
Technical documentationcloud.google.com/­bigquery/­docsdeveloper.microsoft.com/­en-us/­accessdoc.quasar.ai/­masterdocs.stardog.com
DeveloperGoogleMicrosoftquasardbStardog-Union
Initial release2010199220092010
Current release1902 (16.0.11328.20222), March 20193.14.1, January 20247.3.0, May 2020
License infoCommercial or Open Sourcecommercialcommercial infoBundled with Microsoft Officecommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensescommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++Java
Server operating systemshostedWindows infoNot a real database server, but making use of DLLsBSD
Linux
OS X
Windows
Linux
macOS
Windows
Data schemeyesyesschema-freeschema-free and OWL/RDFS-schema support
Typing infopredefined data types such as float or dateyesyesyes infointeger and binaryyes
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 infoImport/export of XML data possible
Secondary indexesnoyesyes infowith tagsyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLyesyes infobut not compliant to any SQL standardSQL-like query languageYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsRESTful HTTP/JSON APIADO.NET
DAO
ODBC
OLE DB
HTTP APIGraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
Supported programming languages.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions infoin JavaScriptyes infosince Access 2010 using the ACE-enginenouser defined functions and aggregates, HTTP Server extensions in Java
Triggersnoyes infosince Access 2010 using the ACE-enginenoyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesnonenoneSharding infoconsistent hashingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replication with selectable replication factorMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonowith Hadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency in HA-Cluster
Foreign keys infoReferential integritynoyesnoyes inforelationships in graphs
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 loggingACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infobut no files for transaction loggingyes infoby using LevelDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoTransient modeyes
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 2003Cryptographically strong user authentication and audit trailAccess rights for users and roles

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More resources
Google BigQueryMicrosoft AccessQuasardbStardog
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