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

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

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonCubrid  Xexclude from comparisonGreenplum  Xexclude from comparisonHazelcast  Xexclude from comparisonIBM Db2 Event Store  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 OLTPAnalytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.A widely adopted in-memory data gridDistributed Event Store optimized for Internet of Things use cases
Primary database modelTime Series DBMSRelational DBMSRelational DBMSKey-value storeEvent Store
Time Series DBMS
Secondary database modelsDocument store
Spatial DBMS
Document store infoJSON support with IMDG 3.12
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
Score9.23
Rank#47  Overall
#30  Relational DBMS
Score6.87
Rank#55  Overall
#6  Key-value stores
Score0.23
Rank#316  Overall
#2  Event Stores
#28  Time Series DBMS
Websiteiotdb.apache.orgcubrid.com (korean)
cubrid.org (english)
greenplum.orghazelcast.comwww.ibm.com/­products/­db2-event-store
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlcubrid.org/­manualsdocs.greenplum.orghazelcast.org/­imdg/­docswww.ibm.com/­docs/­en/­db2-event-store
DeveloperApache Software FoundationCUBRID Corporation, CUBRID FoundationPivotal Software Inc.HazelcastIBM
Initial release20182008200520082017
Current release1.1.0, April 202311.0, January 20217.0.0, September 20235.3.6, November 20232.0
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoApache Version 2; commercial licenses availablecommercial infofree developer edition available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++, JavaJavaC and C++
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
Windows
LinuxAll OS with a Java VMLinux infoLinux, macOS, Windows for the developer addition
Data schemeyesyesyesschema-freeyes
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 infosince Version 4.2yes infothe object must implement a serialization strategyno
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLSQL-like query languageyesyesSQL-like query languageyes infothrough the embedded Spark runtime
APIs and other access methodsJDBC
Native API
ADO.NET
JDBC
ODBC
OLE DB
JDBC
ODBC
JCache
JPA
Memcached protocol
RESTful HTTP API
ADO.NET
DB2 Connect
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
C
Java
Perl
Python
R
.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
Server-side scripts infoStored proceduresyesJava Stored Proceduresyesyes infoEvent Listeners, Executor Servicesyes
Triggersyesyesyesyes infoEventsno
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 replicationSource-replica replicationyes infoReplicated MapActive-active shard replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknoyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Foreign keys infoReferential integritynoyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDone or two-phase-commit; repeatable reads; read commitedno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesNo - written data is immutable
Durability infoSupport for making data persistentyesyesyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyesyes
User concepts infoAccess controlyesfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardRole-based access controlfine grained access rights according to SQL-standard

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More resources
Apache IoTDBCubridGreenplumHazelcastIBM Db2 Event Store
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