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DBMS > AnzoGraph DB vs. CouchDB vs. Datomic vs. Google Cloud Datastore

System Properties Comparison AnzoGraph DB vs. CouchDB vs. Datomic vs. Google Cloud Datastore

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NameAnzoGraph DB  Xexclude from comparisonCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"  Xexclude from comparisonDatomic  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 virtualizationA native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform
Primary database modelGraph DBMS
RDF store
Document storeRelational DBMSDocument store
Secondary database modelsSpatial DBMS infousing the Geocouch extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#302  Overall
#24  Graph DBMS
#13  RDF stores
Score7.46
Rank#51  Overall
#7  Document stores
Score1.55
Rank#144  Overall
#67  Relational DBMS
Score4.13
Rank#71  Overall
#12  Document stores
Websitecambridgesemantics.com/­anzographcouchdb.apache.orgwww.datomic.comcloud.google.com/­datastore
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmdocs.couchdb.org/­en/­stabledocs.datomic.comcloud.google.com/­datastore/­docs
DeveloperCambridge SemanticsApache Software Foundation infoApache top-level project, originally developed by Damien Katz, a former Lotus Notes developerCognitectGoogle
Initial release2018200520122008
Current release2.3, January 20213.3.3, December 20231.0.7180, July 2024
License infoCommercial or Open Sourcecommercial infofree trial version availableOpen Source infoApache version 2commercial infolimited edition freecommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageErlangJava, Clojure
Server operating systemsLinuxAndroid
BSD
Linux
OS X
Solaris
Windows
All OS with a Java VMhosted
Data schemeSchema-free and OWL/RDFS-schema supportschema-freeyesschema-free
Typing infopredefined data types such as float or datenoyesyes, 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.nononono
Secondary indexesnoyes infovia viewsyesyes
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.nonoSQL-like query language (GQL)
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
RESTful HTTP/JSON APIRESTful HTTP APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Supported programming languagesC++
Java
Python
C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk
Clojure
Java
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesView functions in JavaScriptyes infoTransaction Functionsusing Google App Engine
TriggersnoyesBy using transaction functionsCallbacks using the Google Apps Engine
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingSharding infoimproved architecture with release 2.0none infoBut extensive use of caching in the application peersSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-ClusterMulti-source replication
Source-replica replication
none infoBut extensive use of caching in the application peersMulti-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-ClusterEventual ConsistencyImmediate 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 graphsnonoyes infovia ReferenceProperties or Ancestor paths
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno infoatomic operations within a single document possibleACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactions
Concurrency infoSupport for concurrent manipulation of datayesyes infostrategy: optimistic lockingyesyes
Durability infoSupport for making data persistentyesyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes inforecommended only for testing and developmentno
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users can be defined per databasenoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
AnzoGraph DBCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"DatomicGoogle Cloud Datastore
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