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DBMS > Apache IoTDB vs. EsgynDB vs. Ultipa

System Properties Comparison Apache IoTDB vs. EsgynDB vs. Ultipa

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonEsgynDB  Xexclude from comparisonUltipa  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 TrafodionHigh performance Graph DBMS supporting HTAP high availability cluster deployment
Primary database modelTime Series DBMSRelational DBMSGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.19
Rank#176  Overall
#15  Time Series DBMS
Score0.23
Rank#319  Overall
#141  Relational DBMS
Score0.16
Rank#332  Overall
#29  Graph DBMS
Websiteiotdb.apache.orgwww.esgyn.cnwww.ultipa.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.ultipa.com/­document
DeveloperApache Software FoundationEsgynUltipa
Initial release201820152019
Current release1.1.0, April 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++, Java
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
Data schemeyesyes
Typing infopredefined data types such as float or dateyesyes
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.nono
Secondary indexesyesyes
SQL infoSupport of SQLSQL-like query languageyes
APIs and other access methodsJDBC
Native API
ADO.NET
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
All languages supporting JDBC/ODBC/ADO.NetC++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyesJava Stored Procedures
Triggersyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding
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 datacenters
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlyesfine grained access rights according to SQL-standard

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More resources
Apache IoTDBEsgynDBUltipa
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