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DBMS > Drizzle vs. Fujitsu Enterprise Postgres vs. Google Cloud Datastore vs. Kinetica vs. Yanza

System Properties Comparison Drizzle vs. Fujitsu Enterprise Postgres vs. Google Cloud Datastore vs. Kinetica vs. Yanza

Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonKinetica  Xexclude from comparisonYanza  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.Yanza 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.Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformFully vectorized database across both GPUs and CPUsTime Series DBMS for IoT Applications
Primary database modelRelational DBMSRelational DBMSDocument storeRelational DBMSTime Series DBMS
Secondary database modelsDocument store
Spatial DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.37
Rank#278  Overall
#128  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score0.66
Rank#234  Overall
#107  Relational DBMS
Websitewww.postgresql.fastware.comcloud.google.com/­datastorewww.kinetica.comyanza.com
Technical documentationwww.postgresql.fastware.com/­product-manualscloud.google.com/­datastore/­docsdocs.kinetica.com
DeveloperDrizzle project, originally started by Brian AkerPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyGoogleKineticaYanza
Initial release2008200820122015
Current release7.2.4, September 2012Fujitsu Enterprise Postgres 14, January 20227.1, August 2021
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercialcommercialcommercialcommercial infofree version available
Cloud-based only infoOnly available as a cloud servicenonoyesnono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++CC, C++
Server operating systemsFreeBSD
Linux
OS X
Linux
Windows
hostedLinuxWindows
Data schemeyesyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesyes, details hereyesno
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 indexesyesyesyesyesno
SQL infoSupport of SQLyes infowith proprietary extensionsyesSQL-like query language (GQL)SQL-like DML and DDL statementsno
APIs and other access methodsJDBCADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
HTTP API
Supported programming languagesC
C++
Java
PHP
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
any language that supports HTTP calls
Server-side scripts infoStored proceduresnouser defined functionsusing Google App Engineuser defined functionsno
Triggersno infohooks for callbacks inside the server can be used.yesCallbacks using the Google Apps Engineyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesShardingpartitioning by range, list and by hashShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replicationMulti-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 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 configurationImmediate Consistency
Foreign keys infoReferential integrityyesyesyes infovia ReferenceProperties or Ancestor pathsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnono
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
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, HTTPfine grained access rights according to SQL-standardAccess 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
DrizzleFujitsu Enterprise PostgresGoogle Cloud DatastoreKineticaYanza
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