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DBMS > Apache IoTDB vs. Datomic vs. EsgynDB vs. Fujitsu Enterprise Postgres

System Properties Comparison Apache IoTDB vs. Datomic vs. EsgynDB vs. Fujitsu Enterprise Postgres

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonDatomic  Xexclude from comparisonEsgynDB  Xexclude from comparisonFujitsu Enterprise Postgres  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 FlinkDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionEnterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.
Primary database modelTime Series DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score0.31
Rank#285  Overall
#129  Relational DBMS
Websiteiotdb.apache.orgwww.datomic.comwww.esgyn.cnwww.postgresql.fastware.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.datomic.comwww.postgresql.fastware.com/­product-manuals
DeveloperApache Software FoundationCognitectEsgynPostgreSQL Global Development Group, Fujitsu Australia Software Technology
Initial release201820122015
Current release1.1.0, April 20231.0.6735, June 2023Fujitsu Enterprise Postgres 14, January 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infolimited edition freecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava, ClojureC++, JavaC
Server operating systemsAll OS with a Java VM (>= 1.8)All OS with a Java VMLinuxLinux
Windows
Data schemeyesyesyesyes
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.nonono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query languagenoyesyes
APIs and other access methodsJDBC
Native API
RESTful HTTP APIADO.NET
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Clojure
Java
All languages supporting JDBC/ODBC/ADO.Net.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresyesyes infoTransaction FunctionsJava Stored Proceduresuser defined functions
TriggersyesBy using transaction functionsnoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)none infoBut extensive use of caching in the application peersShardingpartitioning by range, list and 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 replicasnone infoBut extensive use of caching in the application peersMulti-source replication between multi datacentersSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes inforecommended only for testing and developmentno
User concepts infoAccess controlyesnofine grained access rights according to SQL-standardfine grained access rights according to SQL-standard
More information provided by the system vendor
Apache IoTDBDatomicEsgynDBFujitsu Enterprise Postgres
Specific characteristics100% compatible with community PostgreSQL
» more
Competitive advantagesBuilt-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
» more
Typical application scenariosTransactional payments applications, reporting and mixed workloads.
» more
Market metricsOver 30 years experience in database technology. Over 20 years in Postgres development...
» more
Licensing and pricing modelsCore based licensing
» more

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Apache IoTDBDatomicEsgynDBFujitsu Enterprise Postgres
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