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DBMS > AnzoGraph DB vs. Axibase vs. Citus vs. Google Cloud Datastore

System Properties Comparison AnzoGraph DB vs. Axibase vs. Citus vs. Google Cloud Datastore

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Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonAxibase  Xexclude from comparisonCitus  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparison
DescriptionScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationScalable TimeSeries DBMS based on HBase with integrated rule engine and visualizationScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform
Primary database modelGraph DBMS
RDF store
Time Series DBMSRelational DBMSDocument store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.29
Rank#303  Overall
#25  Graph DBMS
#14  RDF stores
Score0.35
Rank#282  Overall
#25  Time Series DBMS
Score2.15
Rank#117  Overall
#56  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Websitecambridgesemantics.com/­anzographaxibase.com/­docs/­atsd/­financewww.citusdata.comcloud.google.com/­datastore
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmdocs.citusdata.comcloud.google.com/­datastore/­docs
DeveloperCambridge SemanticsAxibase CorporationGoogle
Initial release2018201320102008
Current release2.3, January 2021155858.1, December 2018
License infoCommercial or Open Sourcecommercial infofree trial version availablecommercial infoCommunity Edition (single node) is free, Enterprise Edition (distributed) is paidOpen Source infoAGPL, commercial license also availablecommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC
Server operating systemsLinuxLinuxLinuxhosted
Data schemeSchema-free and OWL/RDFS-schema supportyesyesschema-free
Typing infopredefined data types such as float or dateyes infoshort, integer, long, float, double, decimal, stringyesyes, details here
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.nonoyes infospecific XML type available, but no XML query functionalityno
Secondary indexesnonoyesyes
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.SQL-like query languageyes infostandard, with numerous extensionsSQL-like query language (GQL)
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
JDBC
Proprietary protocol (Network API)
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Supported programming languagesC++
Java
Python
Go
Java
PHP
Python
R
Ruby
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.using Google App Engine
TriggersnoyesyesCallbacks using the Google Apps Engine
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-ClusterSource-replica replicationSource-replica replication infoother methods possible by using 3rd party extensionsMulti-source replication using Paxos
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingyesnoyes infousing Google Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterImmediate 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.
Foreign keys infoReferential integrityno infonot needed in graphsnoyesyes infovia ReferenceProperties or Ancestor paths
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactions
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.yesnono
User concepts infoAccess controlAccess rights for users and rolesfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
AnzoGraph DBAxibaseCitusGoogle Cloud Datastore
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