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DBMS > Apache Phoenix vs. Greenplum vs. HugeGraph vs. TimescaleDB

System Properties Comparison Apache Phoenix vs. Greenplum vs. HugeGraph vs. TimescaleDB

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGreenplum  Xexclude from comparisonHugeGraph  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseAnalytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.A fast-speed and highly-scalable Graph DBMSA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSRelational DBMSGraph DBMSTime Series DBMS
Secondary database modelsDocument store
Spatial DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score8.37
Rank#48  Overall
#30  Relational DBMS
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitephoenix.apache.orggreenplum.orggithub.com/­hugegraph
hugegraph.apache.org
www.timescale.com
Technical documentationphoenix.apache.orgdocs.greenplum.orghugegraph.apache.org/­docsdocs.timescale.com
DeveloperApache Software FoundationPivotal Software Inc.BaiduTimescale
Initial release2014200520182017
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20197.0.0, September 20230.92.13.0, November 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoApache Version 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC
Server operating systemsLinux
Unix
Windows
LinuxLinux
macOS
Unix
Linux
OS X
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex 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 infosince Version 4.2noyes
Secondary indexesyesyesyes infoalso supports composite index and range indexyes
SQL infoSupport of SQLyesyesnoyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBCJDBC
ODBC
Java API
RESTful HTTP API
TinkerPop Gremlin
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C
Java
Perl
Python
R
Groovy
Java
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functionsyesasynchronous Gremlin script jobsuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replicationyes infodepending on used storage backend, e.g. Cassandra and HBaseSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationyesvia hugegraph-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyes infoedges in graphyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID
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.yesnoyesno
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-standardUsers, roles and permissionsfine grained access rights according to SQL-standard

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More resources
Apache PhoenixGreenplumHugeGraphTimescaleDB
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