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DBMS > AllegroGraph vs. Google BigQuery vs. GridDB vs. Interbase

System Properties Comparison AllegroGraph vs. Google BigQuery vs. GridDB vs. Interbase

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Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonGoogle BigQuery  Xexclude from comparisonGridDB  Xexclude from comparisonInterbase  Xexclude from comparison
DescriptionHigh performance, persistent RDF store with additional support for Graph DBMSLarge scale data warehouse service with append-only tablesScalable in-memory time series database optimized for IoT and Big DataLight-weight proven RDBMS infooriginally from Borland
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Relational DBMSTime Series DBMSRelational DBMS
Secondary database modelsSpatial DBMSKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.06
Rank#187  Overall
#30  Document stores
#17  Graph DBMS
#7  RDF stores
#7  Vector DBMS
Score60.38
Rank#19  Overall
#13  Relational DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score4.61
Rank#72  Overall
#39  Relational DBMS
Websiteallegrograph.comcloud.google.com/­bigquerygriddb.netwww.embarcadero.com/­products/­interbase
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmlcloud.google.com/­bigquery/­docsdocs.griddb.netdocs.embarcadero.com/­products/­interbase
DeveloperFranz Inc.GoogleToshiba CorporationEmbarcadero
Initial release2004201020131984
Current release8.0, December 20235.1, August 2022InterBase 2020, December 2019
License infoCommercial or Open Sourcecommercial infoLimited community edition freecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercial
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 languageC++C
Server operating systemsLinux
OS X
Windows
hostedLinuxAndroid
iOS
Linux
OS X
Windows
Data schemeyes infoRDF schemasyesyesyes
Typing infopredefined data types such as float or dateyesyesyes infonumerical, string, blob, geometry, boolean, timestampyes
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.no infobulk load of XML files possiblenonono infoexport as XML data possible
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSPARQL is used as query languageyesSQL92, SQL-like TQL (Toshiba Query Language)yes
APIs and other access methodsRESTful HTTP API
SPARQL
RESTful HTTP/JSON APIJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby
Server-side scripts infoStored proceduresyes infoJavaScript or Common Lispuser defined functions infoin JavaScriptnoyes infoInterbase procedure and trigger language
Triggersyesnoyesyes
Partitioning methods infoMethods for storing different data on different nodeswith FederationnoneShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replicationInterbase Change Views
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno infoSince BigQuery is designed for querying dataACID at container levelACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoMultiversion concurreny control
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)Access rights for users can be defined per databasefine grained access rights according to SQL-standard
More information provided by the system vendor
AllegroGraphGoogle BigQueryGridDBInterbase
Specific characteristicsKnowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
» more
GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantagesAllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more
1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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