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DBMS > Blazegraph vs. Google Cloud Datastore vs. HugeGraph vs. MarkLogic

System Properties Comparison Blazegraph vs. Google Cloud Datastore vs. HugeGraph vs. MarkLogic

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Editorial information provided by DB-Engines
NameBlazegraph  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHugeGraph  Xexclude from comparisonMarkLogic  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.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA fast-speed and highly-scalable Graph DBMSOperational and transactional Enterprise NoSQL database
Primary database modelGraph DBMS
RDF store
Document storeGraph DBMSDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.75
Rank#219  Overall
#19  Graph DBMS
#8  RDF stores
Score4.47
Rank#76  Overall
#12  Document stores
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score5.92
Rank#58  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#6  Search engines
Websiteblazegraph.comcloud.google.com/­datastoregithub.com/­hugegraph
hugegraph.apache.org
www.marklogic.com
Technical documentationwiki.blazegraph.comcloud.google.com/­datastore/­docshugegraph.apache.org/­docsdocs.marklogic.com
DeveloperBlazegraphGoogleBaiduMarkLogic Corp.
Initial release2006200820182001
Current release2.1.5, March 20190.911.0, December 2022
License infoCommercial or Open SourceOpen Source infoextended commercial license availablecommercialOpen Source infoApache Version 2.0commercial inforestricted free version is available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC++
Server operating systemsLinux
OS X
Windows
hostedLinux
macOS
Unix
Linux
OS X
Windows
Data schemeschema-freeschema-freeyesschema-free infoSchema can be enforced
Typing infopredefined data types such as float or dateyes infoRDF literal typesyes, details hereyesyes
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
Secondary indexesyesyesyes infoalso supports composite index and range indexyes
SQL infoSupport of SQLSPARQL is used as query languageSQL-like query language (GQL)noyes infoSQL92
APIs and other access methodsJava API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
RESTful HTTP API
TinkerPop Gremlin
Java API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
Supported programming languages.Net
C
C++
Java
JavaScript
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Groovy
Java
Python
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresyesusing Google App Engineasynchronous Gremlin script jobsyes infovia XQuery or JavaScript
TriggersnoCallbacks using the Google Apps Enginenoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication using Paxosyes infodepending on used storage backend, e.g. Cassandra and HBaseyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowvia hugegraph-sparkyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate 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 integrityyes infoRelationships in Graphsyes infovia ReferenceProperties or Ancestor pathsyes infoedges in graphno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID infocan act as a resource manager in an XA/JTA transaction
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.noyesyes, with Range Indexes
User concepts infoAccess controlSecurity and Authentication via Web Application Container (Tomcat, Jetty)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users, roles and permissionsRole-based access control at the document and subdocument levels

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More resources
BlazegraphGoogle Cloud DatastoreHugeGraphMarkLogic
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