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DBMS > AllegroGraph vs. Apache Druid vs. Citus vs. Google Cloud Spanner

System Properties Comparison AllegroGraph vs. Apache Druid vs. Citus vs. Google Cloud Spanner

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Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonApache Druid  Xexclude from comparisonCitus  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparison
DescriptionHigh performance, persistent RDF store with additional support for Graph DBMSOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Relational DBMS
Time Series DBMS
Relational DBMSRelational DBMS
Secondary database modelsSpatial DBMSDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.03
Rank#199  Overall
#34  Document stores
#18  Graph DBMS
#7  RDF stores
#7  Vector DBMS
Score3.33
Rank#99  Overall
#51  Relational DBMS
#7  Time Series DBMS
Score2.21
Rank#129  Overall
#61  Relational DBMS
Score3.37
Rank#97  Overall
#50  Relational DBMS
Websiteallegrograph.comdruid.apache.orgwww.citusdata.comcloud.google.com/­spanner
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmldruid.apache.org/­docs/­latest/­designdocs.citusdata.comcloud.google.com/­spanner/­docs
DeveloperFranz Inc.Apache Software Foundation and contributorsGoogle
Initial release2004201220102017
Current release8.0, December 202329.0.0, February 20248.1, December 2018
License infoCommercial or Open Sourcecommercial infoLimited community edition freeOpen Source infoApache license v2Open Source infoAGPL, commercial license also availablecommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC
Server operating systemsLinux
OS X
Windows
Linux
OS X
Unix
Linuxhosted
Data schemeyes infoRDF schemasyes infoschema-less columns are supportedyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 possiblenoyes infospecific XML type available, but no XML query functionalityno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSPARQL is used as query languageSQL for queryingyes infostandard, with numerous extensionsyes infoQuery statements complying to ANSI 2011
APIs and other access methodsRESTful HTTP API
SPARQL
JDBC
RESTful HTTP/JSON API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
Clojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyes infoJavaScript or Common Lispnouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.no
Triggersyesnoyesno
Partitioning methods infoMethods for storing different data on different nodeswith FederationSharding infomanual/auto, time-basedShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yes, via HDFS, S3 or other storage enginesSource-replica replication infoother methods possible by using 3rd party extensionsMulti-source replication with 3 replicas for regional instances.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes infousing Google Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrity
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID infoStrict serializable isolation
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 authenticationRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)
More information provided by the system vendor
AllegroGraphApache DruidCitusGoogle Cloud Spanner
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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More resources
AllegroGraphApache DruidCitusGoogle Cloud Spanner
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