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DBMS > Apache IoTDB vs. IBM Db2 Event Store vs. mSQL vs. OrigoDB vs. VelocityDB

System Properties Comparison Apache IoTDB vs. IBM Db2 Event Store vs. mSQL vs. OrigoDB vs. VelocityDB

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonmSQL infoMini SQL  Xexclude from comparisonOrigoDB  Xexclude from comparisonVelocityDB  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 FlinkDistributed Event Store optimized for Internet of Things use casesmSQL (Mini SQL) is a simple and lightweight RDBMSA fully ACID in-memory object graph databaseA .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)
Primary database modelTime Series DBMSEvent Store
Time Series DBMS
Relational DBMSDocument store
Object oriented DBMS
Graph DBMS
Object oriented DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score1.27
Rank#167  Overall
#77  Relational DBMS
Score0.00
Rank#383  Overall
#53  Document stores
#20  Object oriented DBMS
Score0.05
Rank#358  Overall
#36  Graph DBMS
#16  Object oriented DBMS
Websiteiotdb.apache.orgwww.ibm.com/­products/­db2-event-storehughestech.com.au/­products/­msqlorigodb.comvelocitydb.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.ibm.com/­docs/­en/­db2-event-storeorigodb.com/­docsvelocitydb.com/­UserGuide
DeveloperApache Software FoundationIBMHughes TechnologiesRobert Friberg et alVelocityDB Inc
Initial release2018201719942009 infounder the name LiveDB2011
Current release1.1.0, April 20232.04.4, October 20217.x
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infofree developer edition availablecommercial infofree licenses can be providedOpen Sourcecommercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++CC#C#
Server operating systemsAll OS with a Java VM (>= 1.8)Linux infoLinux, macOS, Windows for the developer additionAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Linux
Windows
Any that supports .NET
Data schemeyesyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesUser defined using .NET types and collectionsyes
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 infocan be achieved using .NETno
Secondary indexesyesnoyesyesyes
SQL infoSupport of SQLSQL-like query languageyes infothrough the embedded Spark runtimeA subset of ANSI SQL is implemented infono subqueries, aggregate functions, views, foreign keys, triggersnono
APIs and other access methodsJDBC
Native API
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
.NET Client API
HTTP API
LINQ
.Net
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
C
C++
Delphi
Java
Perl
PHP
Tcl
.Net.Net
Server-side scripts infoStored proceduresyesyesnoyesno
Triggersyesnonoyes infoDomain EventsCallbacks are triggered when data changes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Shardingnonehorizontal partitioning infoclient side managed; servers are not synchronizedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasActive-active shard replicationnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual ConsistencynoneImmediate Consistency
Foreign keys infoReferential integritynononodepending on modelno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesNo - written data is immutablenoyesyes
Durability infoSupport for making data persistentyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyesyes infoWrite ahead logyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyesyes
User concepts infoAccess controlyesfine grained access rights according to SQL-standardnoRole based authorizationBased on Windows Authentication

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More resources
Apache IoTDBIBM Db2 Event StoremSQL infoMini SQLOrigoDBVelocityDB
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