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DBMS > Blazegraph vs. CouchDB vs. Google Cloud Datastore vs. Linter

System Properties Comparison Blazegraph vs. CouchDB vs. Google Cloud Datastore vs. Linter

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Editorial information provided by DB-Engines
NameBlazegraph  Xexclude from comparisonCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonLinter  Xexclude from comparison
Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.
DescriptionHigh-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformRDBMS for high security requirements
Primary database modelGraph DBMS
RDF store
Document storeDocument storeRelational DBMS
Secondary database modelsSpatial DBMS infousing the Geocouch extensionSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.81
Rank#213  Overall
#19  Graph DBMS
#8  RDF stores
Score8.30
Rank#47  Overall
#7  Document stores
Score4.36
Rank#72  Overall
#12  Document stores
Score0.12
Rank#350  Overall
#152  Relational DBMS
Websiteblazegraph.comcouchdb.apache.orgcloud.google.com/­datastorelinter.ru
Technical documentationwiki.blazegraph.comdocs.couchdb.org/­en/­stablecloud.google.com/­datastore/­docs
DeveloperBlazegraphApache Software Foundation infoApache top-level project, originally developed by Damien Katz, a former Lotus Notes developerGooglerelex.ru
Initial release2006200520081990
Current release2.1.5, March 20193.3.3, December 2023
License infoCommercial or Open SourceOpen Source infoextended commercial license availableOpen Source infoApache version 2commercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaErlangC and C++
Server operating systemsLinux
OS X
Windows
Android
BSD
Linux
OS X
Solaris
Windows
hostedAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Data schemeschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyes infoRDF literal typesnoyes, details hereyes
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.nonono
Secondary indexesyesyes infovia viewsyesyes
SQL infoSupport of SQLSPARQL is used as query languagenoSQL-like query language (GQL)yes
APIs and other access methodsJava API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
RESTful HTTP/JSON APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
Supported programming languages.Net
C
C++
Java
JavaScript
PHP
Python
Ruby
C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
Server-side scripts infoStored proceduresyesView functions in JavaScriptusing Google App Engineyes infoproprietary syntax with the possibility to convert from PL/SQL
TriggersnoyesCallbacks using the Google Apps Engineyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoimproved architecture with release 2.0Shardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
Multi-source replication using PaxosSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationEventual 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
Foreign keys infoReferential integrityyes infoRelationships in Graphsnoyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno infoatomic operations within a single document possibleACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyes infostrategy: optimistic lockingyesyes
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.nono
User concepts infoAccess controlSecurity and Authentication via Web Application Container (Tomcat, Jetty)Access rights for users can be defined per databaseAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standard

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More resources
BlazegraphCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"Google Cloud DatastoreLinter
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