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DBMS > Drizzle vs. Geode vs. Kinetica vs. Microsoft Azure Data Explorer vs. RavenDB

System Properties Comparison Drizzle vs. Geode vs. Kinetica vs. Microsoft Azure Data Explorer vs. RavenDB

Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonGeode  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRavenDB  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.Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesFully vectorized database across both GPUs and CPUsFully managed big data interactive analytics platformOpen Source Operational and Transactional Enterprise NoSQL Document Database
Primary database modelRelational DBMSKey-value storeRelational DBMSRelational DBMS infocolumn orientedDocument store
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
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.86
Rank#134  Overall
#24  Key-value stores
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score2.84
Rank#101  Overall
#18  Document stores
Websitegeode.apache.orgwww.kinetica.comazure.microsoft.com/­services/­data-explorerravendb.net
Technical documentationgeode.apache.org/­docsdocs.kinetica.comdocs.microsoft.com/­en-us/­azure/­data-explorerravendb.net/­docs
DeveloperDrizzle project, originally started by Brian AkerOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.KineticaMicrosoftHibernating Rhinos
Initial release20082002201220192010
Current release7.2.4, September 20121.1, February 20177.1, August 2021cloud service with continuous releases5.4, July 2022
License infoCommercial or Open SourceOpen Source infoGNU GPLOpen Source infoApache Version 2; commercial licenses available as GemfirecommercialcommercialOpen Source infoAGPL version 3, commercial license available
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaC, C++C#
Server operating systemsFreeBSD
Linux
OS X
All OS with a Java VM infothe JDK (8 or later) is also requiredLinuxhostedLinux
macOS
Raspberry Pi
Windows
Data schemeyesschema-freeyesFixed schema with schema-less datatypes (dynamic)schema-free
Typing infopredefined data types such as float or dateyesyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesno
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.nonoyes
Secondary indexesyesnoyesall fields are automatically indexedyes
SQL infoSupport of SQLyes infowith proprietary extensionsSQL-like query language (OQL)SQL-like DML and DDL statementsKusto Query Language (KQL), SQL subsetSQL-like query language (RQL)
APIs and other access methodsJDBCJava Client API
Memcached protocol
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
Supported programming languagesC
C++
Java
PHP
.Net
All JVM based languages
C++
Groovy
Java
Scala
C++
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresnouser defined functionsuser defined functionsYes, possible languages: KQL, Python, Ryes
Triggersno infohooks for callbacks inside the server can be used.yes infoCache Event Listenersyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
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 replicationSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.
Foreign keys infoReferential integrityyesnoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyes, on a single nodenonoACID, Cluster-wide transaction available
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.yesyes infoGPU vRAM or System RAMno
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights per client and object definableAccess rights for users and roles on table levelAzure Active Directory AuthenticationAuthorization levels configured per client per database

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More resources
DrizzleGeodeKineticaMicrosoft Azure Data ExplorerRavenDB
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