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DBMS > Citus vs. Drizzle vs. Geode vs. Hazelcast

System Properties Comparison Citus vs. Drizzle vs. Geode vs. Hazelcast

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Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonDrizzle  Xexclude from comparisonGeode  Xexclude from comparisonHazelcast  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.
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLMySQL 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 processesA widely adopted in-memory data grid
Primary database modelRelational DBMSRelational DBMSKey-value storeKey-value store
Secondary database modelsDocument storeDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score1.92
Rank#131  Overall
#23  Key-value stores
Score5.97
Rank#57  Overall
#6  Key-value stores
Websitewww.citusdata.comgeode.apache.orghazelcast.com
Technical documentationdocs.citusdata.comgeode.apache.org/­docshazelcast.org/­imdg/­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.Hazelcast
Initial release2010200820022008
Current release8.1, December 20187.2.4, September 20121.1, February 20175.3.6, November 2023
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availableOpen Source infoGNU GPLOpen Source infoApache Version 2; commercial licenses available as GemfireOpen Source infoApache Version 2; commercial licenses available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCC++JavaJava
Server operating systemsLinuxFreeBSD
Linux
OS X
All OS with a Java VM infothe JDK (8 or later) is also requiredAll OS with a Java VM
Data schemeyesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyesyes
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.yes infospecific XML type available, but no XML query functionalitynoyes infothe object must implement a serialization strategy
Secondary indexesyesyesnoyes
SQL infoSupport of SQLyes infostandard, with numerous extensionsyes infowith proprietary extensionsSQL-like query language (OQL)SQL-like query language
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBCJava Client API
Memcached protocol
RESTful HTTP API
JCache
JPA
Memcached protocol
RESTful HTTP API
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C++
Java
PHP
.Net
All JVM based languages
C++
Groovy
Java
Scala
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.nouser defined functionsyes infoEvent Listeners, Executor Services
Triggersyesno infohooks for callbacks inside the server can be used.yes infoCache Event Listenersyes infoEvents
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsMulti-source replication
Source-replica replication
Multi-source replicationyes infoReplicated Map
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus Algorithm
Foreign keys infoReferential integrityyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDyes, on a single nodeone or two-phase-commit; repeatable reads; read commited
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.noyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights per client and object definableRole-based access control

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