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DBMS > Drizzle vs. Google Cloud Datastore vs. Hyprcubd vs. Kinetica vs. RDF4J

System Properties Comparison Drizzle vs. Google Cloud Datastore vs. Hyprcubd vs. Kinetica vs. RDF4J

Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHyprcubd  Xexclude from comparisonKinetica  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformServerless Time Series DBMSFully 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 DBMSDocument storeTime Series DBMSRelational DBMSRDF store
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Websitecloud.google.com/­datastorehyprcubd.com (offline)www.kinetica.comrdf4j.org
Technical documentationcloud.google.com/­datastore/­docsdocs.kinetica.comrdf4j.org/­documentation
DeveloperDrizzle project, originally started by Brian AkerGoogleHyprcubd, Inc.KineticaSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2008200820122004
Current release7.2.4, September 20127.1, August 2021
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercialcommercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++GoC, C++Java
Server operating systemsFreeBSD
Linux
OS X
hostedhostedLinuxLinux
OS X
Unix
Windows
Data schemeyesschema-freeyesyesyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyes, details hereyes infotime, int, uint, float, stringyesyes
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 indexesyesyesnoyesyes
SQL infoSupport of SQLyes infowith proprietary extensionsSQL-like query language (GQL)SQL-like query languageSQL-like DML and DDL statementsno
APIs and other access methodsJDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
gRPC (https)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 languagesC
C++
Java
PHP
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
Java
PHP
Python
Server-side scripts infoStored proceduresnousing Google App Enginenouser defined functionsyes
Triggersno infohooks for callbacks inside the server can be used.Callbacks using the Google Apps Enginenoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication using PaxosSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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 or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesyes 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 TransactionsnonoACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesnoyesyes
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 controlPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)token accessAccess rights for users and roles on table levelno

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More resources
DrizzleGoogle Cloud DatastoreHyprcubdKineticaRDF4J infoformerly known as Sesame
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