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DBMS > Apache IoTDB vs. Apache Phoenix vs. IBM Db2 warehouse vs. Microsoft Azure Synapse Analytics vs. PostgreSQL

System Properties Comparison Apache IoTDB vs. Apache Phoenix vs. IBM Db2 warehouse vs. Microsoft Azure Synapse Analytics vs. PostgreSQL

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonApache Phoenix  Xexclude from comparisonIBM Db2 warehouse infoformerly named IBM dashDB  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonPostgreSQL  Xexclude from comparison
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkA scale-out RDBMS with evolutionary schema built on Apache HBaseCloud-based data warehousing serviceElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL
Primary database modelTime Series DBMSRelational DBMSRelational DBMSRelational DBMSRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.
Secondary database modelsDocument store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score1.30
Rank#164  Overall
#75  Relational DBMS
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score645.54
Rank#4  Overall
#4  Relational DBMS
Websiteiotdb.apache.orgphoenix.apache.orgwww.ibm.com/­products/­db2/­warehouseazure.microsoft.com/­services/­synapse-analyticswww.postgresql.org
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlphoenix.apache.orgdocs.microsoft.com/­azure/­synapse-analyticswww.postgresql.org/­docs
DeveloperApache Software FoundationApache Software FoundationIBMMicrosoftPostgreSQL Global Development Group infowww.postgresql.org/­developer
Initial release20182014201420161989 info1989: Postgres, 1996: PostgreSQL
Current release1.1.0, April 20235.0-HBase2, July 2018 and 4.15-HBase1, December 201916.3, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0commercialcommercialOpen Source infoBSD
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC++C
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
Unix
Windows
hostedhostedFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Data schemeyesyes infolate-bound, schema-on-read capabilitiesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.nonono infoImport/export of XML data possiblenoyes infospecific XML-type available, but no XML query functionality.
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLSQL-like query languageyesyesyesyes infostandard with numerous extensions
APIs and other access methodsJDBC
Native API
JDBC.NET Client API
JDBC
ODBC
OLE DB
ADO.NET
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
C#
Java
PHP
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresyesuser defined functionsPL/SQL, SQL PLTransact SQLuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.
Triggersyesnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingSharding, horizontal partitioningpartitioning by range, list and (since PostgreSQL 11) by hash
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasMulti-source replication
Source-replica replication
yesyesSource-replica replication infoother methods possible by using 3rd party extensions
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparkHadoop integrationnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesno
User concepts infoAccess controlyesAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyfine grained access rights according to SQL-standardyesfine grained access rights according to SQL-standard

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More resources
Apache IoTDBApache PhoenixIBM Db2 warehouse infoformerly named IBM dashDBMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehousePostgreSQL
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