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DBMS > Drizzle vs. IBM Cloudant vs. Kinetica vs. Microsoft Azure Data Explorer vs. Oracle NoSQL

System Properties Comparison Drizzle vs. IBM Cloudant vs. Kinetica vs. Microsoft Azure Data Explorer vs. Oracle NoSQL

Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonIBM Cloudant  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOracle NoSQL  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.Database as a Service offering based on Apache CouchDBFully vectorized database across both GPUs and CPUsFully managed big data interactive analytics platformA multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes
Primary database modelRelational DBMSDocument storeRelational DBMSRelational DBMS infocolumn orientedDocument store
Key-value store
Relational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Document store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.68
Rank#106  Overall
#20  Document stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score2.95
Rank#100  Overall
#17  Document stores
#17  Key-value stores
#50  Relational DBMS
Websitewww.ibm.com/­products/­cloudantwww.kinetica.comazure.microsoft.com/­services/­data-explorerwww.oracle.com/­database/­nosql/­technologies/­nosql
Technical documentationcloud.ibm.com/­docs/­Cloudantdocs.kinetica.comdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.oracle.com/­en/­database/­other-databases/­nosql-database/­index.html
DeveloperDrizzle project, originally started by Brian AkerIBM, Apache Software Foundation infoIBM acquired Cloudant in February 2014KineticaMicrosoftOracle
Initial release20082010201220192011
Current release7.2.4, September 20127.1, August 2021cloud service with continuous releases23.3, December 2023
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercialcommercialcommercialOpen Source infoProprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)
Cloud-based only infoOnly available as a cloud servicenoyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++ErlangC, C++Java
Server operating systemsFreeBSD
Linux
OS X
hostedLinuxhostedLinux
Solaris SPARC/x86
Data schemeyesschema-freeyesFixed schema with schema-less datatypes (dynamic)Support Fixed schema and Schema-less deployment with the ability to interoperate between them.
Typing infopredefined data types such as float or dateyesnoyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesoptional
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.nonoyesno
Secondary indexesyesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLyes infowith proprietary extensionsnoSQL-like DML and DDL statementsKusto Query Language (KQL), SQL subsetSQL-like DML and DDL statements
APIs and other access methodsJDBCRESTful HTTP/JSON APIJDBC
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP API
Supported programming languagesC
C++
Java
PHP
C#
Java
JavaScript
Objective-C
PHP
Ruby
C++
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C#
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnoView functions (Map-Reduce) in JavaScriptuser defined functionsYes, possible languages: KQL, Python, Rno
Triggersno infohooks for callbacks inside the server can be used.yesyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
Source-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkwith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency infodepending on configuration
Foreign keys infoReferential integrityyesnoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno infoatomic operations within a document possiblenonoconfigurable infoACID within a storage node (=shard)
Concurrency infoSupport for concurrent manipulation of datayesyes infoOptimistic lockingyesyesyes
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 RAMnoyes infooff heap cache
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users can be defined per databaseAccess rights for users and roles on table levelAzure Active Directory AuthenticationAccess rights for users and roles

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More resources
DrizzleIBM CloudantKineticaMicrosoft Azure Data ExplorerOracle NoSQL
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