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DBMS > Apache Druid vs. Blazegraph vs. Google Cloud Datastore vs. Kinetica vs. RDF4J

System Properties Comparison Apache Druid vs. Blazegraph vs. Google Cloud Datastore vs. Kinetica vs. RDF4J

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonBlazegraph  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonKinetica  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataHigh-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 PlatformFully vectorized database across both GPUs and CPUsRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelRelational DBMS
Time Series DBMS
Graph DBMS
RDF store
Document storeRelational DBMSRDF store
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.29
Rank#95  Overall
#49  Relational DBMS
#7  Time Series DBMS
Score0.77
Rank#222  Overall
#20  Graph DBMS
#8  RDF stores
Score4.49
Rank#79  Overall
#12  Document stores
Score0.69
Rank#234  Overall
#107  Relational DBMS
Score0.71
Rank#231  Overall
#9  RDF stores
Websitedruid.apache.orgblazegraph.comcloud.google.com/­datastorewww.kinetica.comrdf4j.org
Technical documentationdruid.apache.org/­docs/­latest/­designwiki.blazegraph.comcloud.google.com/­datastore/­docsdocs.kinetica.comrdf4j.org/­documentation
DeveloperApache Software Foundation and contributorsBlazegraphGoogleKineticaSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release20122006200820122004
Current release29.0.1, April 20242.1.5, March 20197.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoextended commercial license availablecommercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC, C++Java
Server operating systemsLinux
OS X
Unix
Linux
OS X
Windows
hostedLinuxLinux
OS X
Unix
Windows
Data schemeyes infoschema-less columns are supportedschema-freeschema-freeyesyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyes 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.nonono
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLSQL for queryingSPARQL is used as query languageSQL-like query language (GQL)SQL-like DML and DDL statementsno
APIs and other access methodsJDBC
RESTful HTTP/JSON API
Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
C
C++
Java
JavaScript
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
Java
PHP
Python
Server-side scripts infoStored proceduresnoyesusing Google App Engineuser defined functionsyes
TriggersnonoCallbacks using the Google Apps Engineyes infotriggers when inserted values for one or more columns fall within a specified rangeyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyesMulti-source replication using PaxosSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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 depending on configuration
Foreign keys infoReferential integritynoyes infoRelationships in Graphsyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoin-memory storage is supported as well
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes infoGPU vRAM or System RAM
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemSecurity 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 and roles on table levelno

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More resources
Apache DruidBlazegraphGoogle Cloud DatastoreKineticaRDF4J infoformerly known as Sesame
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