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DBMS > AnzoGraph DB vs. Google Cloud Datastore vs. IBM Cloudant vs. TigerGraph vs. Tkrzw

System Properties Comparison AnzoGraph DB vs. Google Cloud Datastore vs. IBM Cloudant vs. TigerGraph vs. Tkrzw

Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonIBM Cloudant  Xexclude from comparisonTigerGraph  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformDatabase as a Service offering based on Apache CouchDBA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-timeA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelGraph DBMS
RDF store
Document storeDocument storeGraph DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.23
Rank#307  Overall
#24  Graph DBMS
#13  RDF stores
Score4.47
Rank#76  Overall
#12  Document stores
Score2.68
Rank#106  Overall
#20  Document stores
Score1.83
Rank#139  Overall
#13  Graph DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitecambridgesemantics.com/­anzographcloud.google.com/­datastorewww.ibm.com/­products/­cloudantwww.tigergraph.comdbmx.net/­tkrzw
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmcloud.google.com/­datastore/­docscloud.ibm.com/­docs/­Cloudantdocs.tigergraph.com
DeveloperCambridge SemanticsGoogleIBM, Apache Software Foundation infoIBM acquired Cloudant in February 2014Mikio Hirabayashi
Initial release20182008201020172020
Current release2.3, January 20210.9.3, August 2020
License infoCommercial or Open Sourcecommercial infofree trial version availablecommercialcommercialcommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageErlangC++C++
Server operating systemsLinuxhostedhostedLinuxLinux
macOS
Data schemeSchema-free and OWL/RDFS-schema supportschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or dateyes, details herenoyesno
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.nonononono
Secondary indexesnoyesyes
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.SQL-like query language (GQL)noSQL-like query language (GSQL)no
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP/JSON APIGSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languagesC++
Java
Python
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
Java
JavaScript
Objective-C
PHP
Ruby
C++
Java
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesusing Google App EngineView functions (Map-Reduce) in JavaScriptyesno
TriggersnoCallbacks using the Google Apps Engineyesnono
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-ClusterMulti-source replication using PaxosMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingyes infousing Google Cloud Dataflowyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterImmediate 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.Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infonot needed in graphsyes infovia ReferenceProperties or Ancestor pathsnoyes infoRelationships in graphsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsno infoatomic operations within a document possibleACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoOptimistic lockingyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnononoyes infousing specific database classes
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users can be defined per databaseRole-based access controlno

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More resources
AnzoGraph DBGoogle Cloud DatastoreIBM CloudantTigerGraphTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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