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DBMS > Apache IoTDB vs. Cubrid vs. Firebase Realtime Database vs. Hazelcast vs. IBM Db2 Event Store

System Properties Comparison Apache IoTDB vs. Cubrid vs. Firebase Realtime Database vs. Hazelcast vs. IBM Db2 Event Store

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonCubrid  Xexclude from comparisonFirebase Realtime Database  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 OLTPCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.A widely adopted in-memory data gridDistributed Event Store optimized for Internet of Things use cases
Primary database modelTime Series DBMSRelational DBMSDocument storeKey-value storeEvent Store
Time Series DBMS
Secondary database modelsDocument 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
Score15.00
Rank#39  Overall
#6  Document stores
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)
firebase.google.com/­products/­realtime-databasehazelcast.comwww.ibm.com/­products/­db2-event-store
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlcubrid.org/­manualsfirebase.google.com/­docs/­databasehazelcast.org/­imdg/­docswww.ibm.com/­docs/­en/­db2-event-store
DeveloperApache Software FoundationCUBRID Corporation, CUBRID FoundationGoogle infoacquired by Google 2014HazelcastIBM
Initial release20182008201220082017
Current release1.1.0, April 202311.0, January 20215.3.6, November 20232.0
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0commercialOpen Source infoApache Version 2; commercial licenses availablecommercial infofree developer edition available
Cloud-based only infoOnly available as a cloud servicenonoyesnono
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
hostedAll OS with a Java VMLinux infoLinux, macOS, Windows for the developer addition
Data schemeyesyesschema-freeschema-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.nononoyes infothe object must implement a serialization strategyno
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLSQL-like query languageyesnoSQL-like query languageyes infothrough the embedded Spark runtime
APIs and other access methodsJDBC
Native API
ADO.NET
JDBC
ODBC
OLE DB
Android
iOS
JavaScript API
RESTful HTTP API
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
Java
JavaScript
Objective-C
.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 Procedureslimited functionality with using 'rules'yes infoEvent Listeners, Executor Servicesyes
TriggersyesyesCallbacks are triggered when data changesyes infoEventsno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)noneShardingSharding
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 replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDyesone 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.yesnoyesyes
User concepts infoAccess controlyesfine grained access rights according to SQL-standardyes, based on authentication and database rulesRole-based access controlfine grained access rights according to SQL-standard

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More resources
Apache IoTDBCubridFirebase Realtime DatabaseHazelcastIBM Db2 Event Store
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