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DBMS > Drizzle vs. Google Cloud Datastore vs. IBM Cloudant vs. Kinetica

System Properties Comparison Drizzle vs. Google Cloud Datastore vs. IBM Cloudant vs. Kinetica

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonIBM Cloudant  Xexclude from comparisonKinetica  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.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformDatabase as a Service offering based on Apache CouchDBFully vectorized database across both GPUs and CPUs
Primary database modelRelational DBMSDocument storeDocument storeRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.49
Rank#79  Overall
#12  Document stores
Score2.73
Rank#108  Overall
#20  Document stores
Score0.69
Rank#234  Overall
#107  Relational DBMS
Websitecloud.google.com/­datastorewww.ibm.com/­products/­cloudantwww.kinetica.com
Technical documentationcloud.google.com/­datastore/­docscloud.ibm.com/­docs/­Cloudantdocs.kinetica.com
DeveloperDrizzle project, originally started by Brian AkerGoogleIBM, Apache Software Foundation infoIBM acquired Cloudant in February 2014Kinetica
Initial release2008200820102012
Current release7.2.4, September 20127.1, August 2021
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++ErlangC, C++
Server operating systemsFreeBSD
Linux
OS X
hostedhostedLinux
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyes, details herenoyes
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 indexesyesyesyesyes
SQL infoSupport of SQLyes infowith proprietary extensionsSQL-like query language (GQL)noSQL-like DML and DDL statements
APIs and other access methodsJDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP/JSON APIJDBC
ODBC
RESTful HTTP API
Supported programming languagesC
C++
Java
PHP
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
Java
JavaScript
Objective-C
PHP
Ruby
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnousing Google App EngineView functions (Map-Reduce) in JavaScriptuser defined functions
Triggersno infohooks for callbacks inside the server can be used.Callbacks using the Google Apps Engineyesyes 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 nodesMulti-source replication
Source-replica replication
Multi-source replication using PaxosMulti-source replication
Source-replica replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyesno
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 Transactionsno infoatomic operations within a document possibleno
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoOptimistic lockingyes
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.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)Access rights for users can be defined per databaseAccess rights for users and roles on table level

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More resources
DrizzleGoogle Cloud DatastoreIBM CloudantKinetica
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