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DBMS > Apache Phoenix vs. Citus vs. GeoSpock vs. HarperDB

System Properties Comparison Apache Phoenix vs. Citus vs. GeoSpock vs. HarperDB

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonCitus  Xexclude from comparisonGeoSpock  Xexclude from comparisonHarperDB  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLSpatial and temporal data processing engine for extreme data scaleUltra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.
Primary database modelRelational DBMSRelational DBMSRelational DBMSDocument store
Secondary database modelsDocument storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score0.55
Rank#248  Overall
#38  Document stores
Websitephoenix.apache.orgwww.citusdata.comgeospock.comwww.harperdb.io
Technical documentationphoenix.apache.orgdocs.citusdata.comdocs.harperdb.io/­docs
DeveloperApache Software FoundationGeoSpockHarperDB
Initial release201420102017
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20198.1, December 20182.0, September 20193.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoAGPL, commercial license also availablecommercialcommercial infofree community edition available
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCJava, JavascriptNode.js
Server operating systemsLinux
Unix
Windows
LinuxhostedLinux
OS X
Data schemeyes infolate-bound, schema-on-read capabilitiesyesyesdynamic schema
Typing infopredefined data types such as float or dateyesyesyesyes infoJSON data types
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.noyes infospecific XML type available, but no XML query functionalitynono
Secondary indexesyesyestemporal, categoricalyes
SQL infoSupport of SQLyesyes infostandard, with numerous extensionsANSI SQL for query only (using Presto)SQL-like data manipulation statements
APIs and other access methodsJDBCADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBCJDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
Server-side scripts infoStored proceduresuser defined functionsuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.noCustom Functions infosince release 3.1
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingAutomatic shardingA table resides as a whole on one (or more) nodes in a cluster
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replication infoother methods possible by using 3rd party extensionsyes infothe nodes on which a table resides can be defined
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoAtomic execution of specific operations
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes, using LMDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyfine grained access rights according to SQL-standardAccess rights for users can be defined per tableAccess rights for users and roles

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More resources
Apache PhoenixCitusGeoSpockHarperDB
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