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DBMS > Apache IoTDB vs. Elasticsearch vs. EsgynDB vs. Fujitsu Enterprise Postgres vs. SiteWhere

System Properties Comparison Apache IoTDB vs. Elasticsearch vs. EsgynDB vs. Fujitsu Enterprise Postgres vs. SiteWhere

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonElasticsearch  Xexclude from comparisonEsgynDB  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonSiteWhere  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 distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricEnterprise-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.M2M integration platform for persisting/querying time series data
Primary database modelTime Series DBMSSearch engineRelational DBMSRelational DBMSTime Series DBMS
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score132.83
Rank#7  Overall
#1  Search engines
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score0.37
Rank#278  Overall
#128  Relational DBMS
Score0.06
Rank#383  Overall
#43  Time Series DBMS
Websiteiotdb.apache.orgwww.elastic.co/­elasticsearchwww.esgyn.cnwww.postgresql.fastware.comgithub.com/­sitewhere/­sitewhere
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlwww.postgresql.fastware.com/­product-manualssitewhere1.sitewhere.io/­index.html
DeveloperApache Software FoundationElasticEsgynPostgreSQL Global Development Group, Fujitsu Australia Software TechnologySiteWhere
Initial release2018201020152010
Current release1.1.0, April 20238.6, January 2023Fujitsu Enterprise Postgres 14, January 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoElastic LicensecommercialcommercialOpen Source infoCommon Public Attribution License Version 1.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaC++, JavaCJava
Server operating systemsAll OS with a Java VM (>= 1.8)All OS with a Java VMLinuxLinux
Windows
Linux
OS X
Windows
Data schemeyesschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesyespredefined scheme
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.nononono
Secondary indexesyesyes infoAll search fields are automatically indexedyesyesno
SQL infoSupport of SQLSQL-like query languageSQL-like query languageyesyesno
APIs and other access methodsJDBC
Native API
Java API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HTTP REST
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
All languages supporting JDBC/ODBC/ADO.Net.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresyesyesJava Stored Proceduresuser defined functions
Triggersyesyes infoby using the 'percolation' featurenoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingpartitioning by range, list and by hashSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesMulti-source replication between multi datacentersSource-replica replicationselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparkES-Hadoop Connectoryesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
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.yesMemcached and Redis integrationnono
User concepts infoAccess controlyesfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardUsers with fine-grained authorization concept

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More resources
Apache IoTDBElasticsearchEsgynDBFujitsu Enterprise PostgresSiteWhere
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