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DBMS > Apache IoTDB vs. Cubrid vs. Hazelcast vs. IBM Db2 Event Store vs. Kinetica

System Properties Comparison Apache IoTDB vs. Cubrid vs. Hazelcast vs. IBM Db2 Event Store vs. Kinetica

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonCubrid  Xexclude from comparisonHazelcast  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonKinetica  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 FlinkCUBRID is an open-source SQL-based relational database management system with object extensions for OLTPA widely adopted in-memory data gridDistributed Event Store optimized for Internet of Things use casesFully vectorized database across both GPUs and CPUs
Primary database modelTime Series DBMSRelational DBMSKey-value storeEvent Store
Time Series DBMS
Relational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.19
Rank#176  Overall
#15  Time Series DBMS
Score1.31
Rank#169  Overall
#78  Relational DBMS
Score6.87
Rank#55  Overall
#6  Key-value stores
Score0.23
Rank#316  Overall
#2  Event Stores
#28  Time Series DBMS
Score0.69
Rank#234  Overall
#107  Relational DBMS
Websiteiotdb.apache.orgcubrid.com (korean)
cubrid.org (english)
hazelcast.comwww.ibm.com/­products/­db2-event-storewww.kinetica.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlcubrid.org/­manualshazelcast.org/­imdg/­docswww.ibm.com/­docs/­en/­db2-event-storedocs.kinetica.com
DeveloperApache Software FoundationCUBRID Corporation, CUBRID FoundationHazelcastIBMKinetica
Initial release20182008200820172012
Current release1.1.0, April 202311.0, January 20215.3.6, November 20232.07.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoApache Version 2; commercial licenses availablecommercial infofree developer edition availablecommercial
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 languageJavaC, C++, JavaJavaC and C++C, C++
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
Windows
All OS with a Java VMLinux infoLinux, macOS, Windows for the developer additionLinux
Data schemeyesyesschema-freeyesyes
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.nonoyes infothe object must implement a serialization strategynono
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLSQL-like query languageyesSQL-like query languageyes infothrough the embedded Spark runtimeSQL-like DML and DDL statements
APIs and other access methodsJDBC
Native API
ADO.NET
JDBC
ODBC
OLE DB
JCache
JPA
Memcached protocol
RESTful HTTP API
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyesJava Stored Proceduresyes infoEvent Listeners, Executor Servicesyesuser defined functions
Triggersyesyesyes infoEventsnoyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)noneShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasSource-replica replicationyes infoReplicated MapActive-active shard replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDone or two-phase-commit; repeatable reads; read commitednono
Concurrency infoSupport for concurrent manipulation of datayesyesyesNo - written data is immutableyes
Durability infoSupport for making data persistentyesyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlyesfine grained access rights according to SQL-standardRole-based access controlfine grained access rights according to SQL-standardAccess rights for users and roles on table level

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More resources
Apache IoTDBCubridHazelcastIBM Db2 Event StoreKinetica
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