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DBMS > Blazegraph vs. Google Cloud Datastore vs. Hive vs. Microsoft Azure Table Storage

System Properties Comparison Blazegraph vs. Google Cloud Datastore vs. Hive vs. Microsoft Azure Table Storage

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Editorial information provided by DB-Engines
NameBlazegraph  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHive  Xexclude from comparisonMicrosoft Azure Table Storage  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 Platformdata warehouse software for querying and managing large distributed datasets, built on HadoopA Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelGraph DBMS
RDF store
Document storeRelational DBMSWide column store
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
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Websiteblazegraph.comcloud.google.com/­datastorehive.apache.orgazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationwiki.blazegraph.comcloud.google.com/­datastore/­docscwiki.apache.org/­confluence/­display/­Hive/­Home
DeveloperBlazegraphGoogleApache Software Foundation infoinitially developed by FacebookMicrosoft
Initial release2006200820122012
Current release2.1.5, March 20193.1.3, April 2022
License infoCommercial or Open SourceOpen Source infoextended commercial license availablecommercialOpen Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud servicenoyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava
Server operating systemsLinux
OS X
Windows
hostedAll OS with a Java VMhosted
Data schemeschema-freeschema-freeyesschema-free
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.nono
Secondary indexesyesyesyesno
SQL infoSupport of SQLSPARQL is used as query languageSQL-like query language (GQL)SQL-like DML and DDL statementsno
APIs and other access methodsJava API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
RESTful HTTP API
Supported programming languages.Net
C
C++
Java
JavaScript
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
PHP
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyesusing Google App Engineyes infouser defined functions and integration of map-reduceno
TriggersnoCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication using Paxosselectable replication factoryes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyes infoquery execution via MapReduceno
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 pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnooptimistic locking
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.nono
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)Access rights for users, groups and rolesAccess rights based on private key authentication or shared access signatures

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More resources
BlazegraphGoogle Cloud DatastoreHiveMicrosoft Azure Table Storage
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