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DBMS > AllegroGraph vs. Citus vs. Google Cloud Datastore vs. InfinityDB

System Properties Comparison AllegroGraph vs. Citus vs. Google Cloud Datastore vs. InfinityDB

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Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonCitus  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonInfinityDB  Xexclude from comparison
DescriptionHigh performance, persistent RDF store with additional support for Graph DBMSScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA Java embedded Key-Value Store which extends the Java Map interface
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Relational DBMSDocument storeKey-value store
Secondary database modelsSpatial DBMSDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.13
Rank#179  Overall
#30  Document stores
#17  Graph DBMS
#7  RDF stores
#7  Vector DBMS
Score2.15
Rank#117  Overall
#56  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score0.08
Rank#365  Overall
#55  Key-value stores
Websiteallegrograph.comwww.citusdata.comcloud.google.com/­datastoreboilerbay.com
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmldocs.citusdata.comcloud.google.com/­datastore/­docsboilerbay.com/­infinitydb/­manual
DeveloperFranz Inc.GoogleBoiler Bay Inc.
Initial release2004201020082002
Current release8.0, December 20238.1, December 20184.0
License infoCommercial or Open Sourcecommercial infoLimited community edition freeOpen Source infoAGPL, commercial license also availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCJava
Server operating systemsLinux
OS X
Windows
LinuxhostedAll OS with a Java VM
Data schemeyes infoRDF schemasyesschema-freeyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgrade
Typing infopredefined data types such as float or dateyesyesyes, details hereyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arrays
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 possibleyes infospecific XML type available, but no XML query functionalitynono
Secondary indexesyesyesyesno infomanual creation possible, using inversions based on multi-value capability
SQL infoSupport of SQLSPARQL is used as query languageyes infostandard, with numerous extensionsSQL-like query language (GQL)no
APIs and other access methodsRESTful HTTP API
SPARQL
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Server-side scripts infoStored proceduresyes infoJavaScript or Common Lispuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.using Google App Engineno
TriggersyesyesCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodeswith FederationShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replication infoother methods possible by using 3rd party extensionsMulti-source replication using Paxosnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency infoREAD-COMMITTED or SERIALIZED
Foreign keys infoReferential integritynoyesyes infovia ReferenceProperties or Ancestor pathsno infomanual creation possible, using inversions based on multi-value capability
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID infoOptimistic locking for transactions; no isolation for bulk loads
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.nononono
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no
More information provided by the system vendor
AllegroGraphCitusGoogle Cloud DatastoreInfinityDB
Specific characteristicsKnowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
» more
Competitive advantagesAllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more
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