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DBMS > Citus vs. Drizzle vs. HBase vs. IRONdb

System Properties Comparison Citus vs. Drizzle vs. HBase vs. IRONdb

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Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonDrizzle  Xexclude from comparisonHBase  Xexclude from comparisonIRONdb  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.IRONdb seems to be discontinued. Therefore it 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.Wide-column store based on Apache Hadoop and on concepts of BigTableA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity
Primary database modelRelational DBMSRelational DBMSWide column storeTime Series DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Websitewww.citusdata.comhbase.apache.orgwww.circonus.com/solutions/time-series-database/
Technical documentationdocs.citusdata.comhbase.apache.org/­book.htmldocs.circonus.com/irondb/category/getting-started
DeveloperDrizzle project, originally started by Brian AkerApache Software Foundation infoApache top-level project, originally developed by PowersetCirconus LLC.
Initial release2010200820082017
Current release8.1, December 20187.2.4, September 20122.3.4, January 2021V0.10.20, January 2018
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availableOpen Source infoGNU GPLOpen Source infoApache version 2commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC++JavaC and C++
Server operating systemsLinuxFreeBSD
Linux
OS X
Linux
Unix
Windows infousing Cygwin
Linux
Data schemeyesyesschema-free, schema definition possibleschema-free
Typing infopredefined data types such as float or dateyesyesoptions to bring your own types, AVROyes infotext, numeric, histograms
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 functionalitynono
Secondary indexesyesyesnono
SQL infoSupport of SQLyes infostandard, with numerous extensionsyes infowith proprietary extensionsnoSQL-like query language (Circonus Analytics Query Language: CAQL)
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBCJava API
RESTful HTTP API
Thrift
HTTP API
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C++
Java
PHP
C
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.noyes infoCoprocessors in Javayes, in Lua
Triggersyesno infohooks for callbacks inside the server can be used.yesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingAutomatic, metric affinity per node
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 replication
Source-replica replication
configurable replication factor, datacenter aware
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyImmediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integrityyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDSingle row ACID (across millions of columns)no
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.noyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACno

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CitusDrizzleHBaseIRONdb
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