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DBMS > Apache Phoenix vs. IBM Db2 Event Store vs. PostgreSQL vs. YottaDB

System Properties Comparison Apache Phoenix vs. IBM Db2 Event Store vs. PostgreSQL vs. YottaDB

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonPostgreSQL  Xexclude from comparisonYottaDB  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseDistributed Event Store optimized for Internet of Things use casesWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQLA fast and solid embedded Key-value store
Primary database modelRelational DBMSEvent Store
Time Series DBMS
Relational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.Key-value store
Secondary database modelsDocument store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
Relational DBMS infousing the Octo plugin
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score0.27
Rank#309  Overall
#2  Event Stores
#28  Time Series DBMS
Score636.25
Rank#4  Overall
#4  Relational DBMS
Score0.28
Rank#306  Overall
#44  Key-value stores
Websitephoenix.apache.orgwww.ibm.com/­products/­db2-event-storewww.postgresql.orgyottadb.com
Technical documentationphoenix.apache.orgwww.ibm.com/­docs/­en/­db2-event-storewww.postgresql.org/­docsyottadb.com/­resources/­documentation
DeveloperApache Software FoundationIBMPostgreSQL Global Development Group infowww.postgresql.org/­developerYottaDB, LLC
Initial release201420171989 info1989: Postgres, 1996: PostgreSQL2001
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20192.016.3, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infofree developer edition availableOpen Source infoBSDOpen Source infoAGPL 3.0
Cloud-based only infoOnly available as a cloud servicenononono
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Implementation languageJavaC and C++CC
Server operating systemsLinux
Unix
Windows
Linux infoLinux, macOS, Windows for the developer additionFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Docker
Linux
Data schemeyes infolate-bound, schema-on-read capabilitiesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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 infospecific XML-type available, but no XML query functionality.no
Secondary indexesyesnoyesno
SQL infoSupport of SQLyesyes infothrough the embedded Spark runtimeyes infostandard with numerous extensionsby using the Octo plugin
APIs and other access methodsJDBCADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
PostgreSQL wire protocol infousing the Octo plugin
Proprietary protocol
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust
Server-side scripts infoStored proceduresuser defined functionsyesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingpartitioning by range, list and (since PostgreSQL 11) by hash
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Active-active shard replicationSource-replica replication infoother methods possible by using 3rd party extensionsyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesNo - written data is immutableyes
Durability infoSupport for making data persistentyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyes
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-standardfine grained access rights according to SQL-standardUsers and groups based on OS-security mechanisms

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Apache PhoenixIBM Db2 Event StorePostgreSQLYottaDB
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