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DBMS > Blazegraph vs. Google Cloud Datastore vs. Hazelcast vs. Kinetica

System Properties Comparison Blazegraph vs. Google Cloud Datastore vs. Hazelcast vs. Kinetica

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Editorial information provided by DB-Engines
NameBlazegraph  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHazelcast  Xexclude from comparisonKinetica  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 widely adopted in-memory data gridFully vectorized database across both GPUs and CPUs
Primary database modelGraph DBMS
RDF store
Document storeKey-value storeRelational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12Spatial DBMS
Time Series DBMS
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
Score5.97
Rank#57  Overall
#6  Key-value stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Websiteblazegraph.comcloud.google.com/­datastorehazelcast.comwww.kinetica.com
Technical documentationwiki.blazegraph.comcloud.google.com/­datastore/­docshazelcast.org/­imdg/­docsdocs.kinetica.com
DeveloperBlazegraphGoogleHazelcastKinetica
Initial release2006200820082012
Current release2.1.5, March 20195.3.6, November 20237.1, August 2021
License infoCommercial or Open SourceOpen Source infoextended commercial license availablecommercialOpen Source infoApache Version 2; commercial licenses availablecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaC, C++
Server operating systemsLinux
OS X
Windows
hostedAll OS with a Java VMLinux
Data schemeschema-freeschema-freeschema-freeyes
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.noyes infothe object must implement a serialization strategyno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSPARQL is used as query languageSQL-like query language (GQL)SQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsJava API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JCache
JPA
Memcached protocol
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
Supported programming languages.Net
C
C++
Java
JavaScript
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyesusing Google App Engineyes infoEvent Listeners, Executor Servicesuser defined functions
TriggersnoCallbacks using the Google Apps Engineyes infoEventsyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication using Paxosyes infoReplicated MapSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyesno
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.Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyes infoRelationships in Graphsyes infovia ReferenceProperties or Ancestor pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsone or two-phase-commit; repeatable reads; read commitedno
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 infoGPU vRAM or System RAM
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)Role-based access controlAccess rights for users and roles on table level

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More resources
BlazegraphGoogle Cloud DatastoreHazelcastKinetica
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