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

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

Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonFirebolt  Xexclude from comparisonGoogle Cloud Datastore  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.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Highly scalable cloud data warehouse and analytics product infoForked from ClickhouseAutomatically 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 DBMSRelational DBMSDocument storeRelational DBMSRDF store
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.90
Rank#134  Overall
#62  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Websitewww.firebolt.iocloud.google.com/­datastorewww.kinetica.comrdf4j.org
Technical documentationdocs.firebolt.iocloud.google.com/­datastore/­docsdocs.kinetica.comrdf4j.org/­documentation
DeveloperDrizzle project, originally started by Brian AkerFirebolt Analytics Inc.GoogleKineticaSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release20082020200820122004
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

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Implementation languageC++C, C++Java
Server operating systemsFreeBSD
Linux
OS X
hostedhostedLinuxLinux
OS X
Unix
Windows
Data schemeyesyesschema-freeyesyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyesyes, 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 indexesyesyesyesyesyes
SQL infoSupport of SQLyes infowith proprietary extensionsyesSQL-like query language (GQL)SQL-like DML and DDL statementsno
APIs and other access methodsJDBC.Net
ODBC
RESTful HTTP API
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 languagesC
C++
Java
PHP
Go
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
Java
PHP
Python
Server-side scripts infoStored proceduresnonousing Google App Engineuser defined functionsyes
Triggersno infohooks for callbacks inside the server can be used.noCallbacks 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 nodesShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
depending on storage layerMulti-source replication using PaxosSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
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.Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes 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.noyes 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)Access rights for users and roles on table levelno

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More resources
DrizzleFireboltGoogle Cloud DatastoreKineticaRDF4J infoformerly known as Sesame
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