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DBMS > Apache IoTDB vs. EDB Postgres vs. TimescaleDB vs. Titan vs. ToroDB

System Properties Comparison Apache IoTDB vs. EDB Postgres vs. TimescaleDB vs. Titan vs. ToroDB

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonEDB Postgres  Xexclude from comparisonTimescaleDB  Xexclude from comparisonTitan  Xexclude from comparisonToroDB  Xexclude from comparison
Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
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 FlinkThe EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLTitan is a Graph DBMS optimized for distributed clusters.A MongoDB-compatible JSON document store, built on top of PostgreSQL
Primary database modelTime Series DBMSRelational DBMSTime Series DBMSGraph DBMSDocument store
Secondary database modelsDocument store
Spatial DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score1.90
Rank#135  Overall
#63  Relational DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websiteiotdb.apache.orgwww.enterprisedb.comwww.timescale.comgithub.com/­thinkaurelius/­titangithub.com/­torodb/­server
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.enterprisedb.com/­docsdocs.timescale.comgithub.com/­thinkaurelius/­titan/­wiki
DeveloperApache Software FoundationEnterpriseDBTimescaleAurelius, owned by DataStax8Kdata
Initial release20182005201720122016
Current release1.1.0, April 202314, December 20212.13.0, November 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infoBSD for PostgreSQL-componentsOpen Source infoApache 2.0Open Source infoApache license, version 2.0Open Source infoAGPL-V3
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCCJavaJava
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
Windows
Linux
OS X
Windows
Linux
OS X
Unix
Windows
All OS with a Java 7 VM
Data schemeyesyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data typesyesyes infostring, integer, double, boolean, date, object_id
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.noyes infospecific XML-type available, but no XML query functionality.yesno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query languageyes infostandard with numerous extensionsyes infofull PostgreSQL SQL syntaxno
APIs and other access methodsJDBC
Native API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Clojure
Java
Python
Server-side scripts infoStored proceduresyesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellyes
Triggersyesyesyesyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)horizontal partitioning infoby hash, list or rangeyes, across time and space (hash partitioning) attributesyes infovia pluggable storage backendsSharding
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 replicationSource-replica replication with hot standby and reads on replicas infoyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknonoyes infovia Faunus, a graph analytics engine
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesyesyes infoRelationships in graphno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcastyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlyesfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardUser authentification and security via Rexster Graph ServerAccess rights for users and roles

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More resources
Apache IoTDBEDB PostgresTimescaleDBTitanToroDB
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