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DBMS > Apache IoTDB vs. EsgynDB vs. Immudb vs. Netezza vs. PostgreSQL

System Properties Comparison Apache IoTDB vs. EsgynDB vs. Immudb vs. Netezza vs. PostgreSQL

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonEsgynDB  Xexclude from comparisonImmudb  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  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 FlinkEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionAn open source immutable (append-only) database with cryptographic verification which makes it tamper-resistant and fully auditable.Data warehouse and analytics appliance part of IBM PureSystemsWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL
Primary database modelTime Series DBMSRelational DBMSKey-value storeRelational DBMSRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.
Secondary database modelsRelational DBMSDocument 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
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score0.24
Rank#305  Overall
#43  Key-value stores
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score645.54
Rank#4  Overall
#4  Relational DBMS
Websiteiotdb.apache.orgwww.esgyn.cngithub.com/­codenotary/­immudb
immudb.io
www.ibm.com/­products/­netezzawww.postgresql.org
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.immudb.iowww.postgresql.org/­docs
DeveloperApache Software FoundationEsgynCodenotaryIBMPostgreSQL Global Development Group infowww.postgresql.org/­developer
Initial release20182015202020001989 info1989: Postgres, 1996: PostgreSQL
Current release1.1.0, April 20231.2.3, April 202216.3, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2.0commercialOpen Source infoBSD
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++, JavaGoC
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxBSD
Linux
macOS
Solaris
Windows
z/OS
Linux infoincluded in applianceFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Data schemeyesyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.nononoyes infospecific XML-type available, but no XML query functionality.
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLSQL-like query languageyesSQL-like syntaxyesyes infostandard with numerous extensions
APIs and other access methodsJDBC
Native API
ADO.NET
JDBC
ODBC
gRPC protocol
PostgreSQL wire protocol
JDBC
ODBC
OLE DB
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
All languages supporting JDBC/ODBC/ADO.Net.Net
Go
Java
JavaScript (Node.js)
Python
C
C++
Fortran
Java
Lua
Perl
Python
R
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresyesJava Stored Proceduresnoyesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.
Triggersyesnononoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingShardingpartitioning 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 between multi datacentersSource-replica replicationSource-replica replication infoother methods possible by using 3rd party extensions
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyesnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnonoyes
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.yesnonono
User concepts infoAccess controlyesfine grained access rights according to SQL-standardUsers with fine-grained authorization conceptfine grained access rights according to SQL-standard

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More resources
Apache IoTDBEsgynDBImmudbNetezza infoAlso called PureData System for Analytics by IBMPostgreSQL
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