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

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

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Editorial information provided by DB-Engines
NameBlazegraph  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonGridGain  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 PlatformGridGain is an in-memory computing platform, built on Apache IgniteFully vectorized database across both GPUs and CPUs
Primary database modelGraph DBMS
RDF store
Document storeKey-value store
Relational DBMS
Relational DBMS
Secondary database modelsSpatial 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
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Websiteblazegraph.comcloud.google.com/­datastorewww.gridgain.comwww.kinetica.com
Technical documentationwiki.blazegraph.comcloud.google.com/­datastore/­docswww.gridgain.com/­docs/­index.htmldocs.kinetica.com
DeveloperBlazegraphGoogleGridGain Systems, Inc.Kinetica
Initial release2006200820072012
Current release2.1.5, March 2019GridGain 8.5.17.1, August 2021
License infoCommercial or Open SourceOpen Source infoextended commercial license availablecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava, C++, .NetC, C++
Server operating systemsLinux
OS X
Windows
hostedLinux
OS X
Solaris
Windows
Linux
Data schemeschema-freeschema-freeyesyes
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.noyesno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSPARQL is used as query languageSQL-like query language (GQL)ANSI-99 for query and DML statements, subset of DDLSQL-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
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
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
C#
C++
Java
PHP
Python
Ruby
Scala
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyesusing Google App Engineyes (compute grid and cache interceptors can be used instead)user defined functions
TriggersnoCallbacks using the Google Apps Engineyes (cache interceptors and events)yes 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 (replicated cache)Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyes (compute grid and hadoop accelerator)no
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 ConsistencyImmediate 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 TransactionsACIDno
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)Security Hooks for custom implementationsAccess rights for users and roles on table level

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More resources
BlazegraphGoogle Cloud DatastoreGridGainKinetica
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