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DBMS > Apache IoTDB vs. DataFS vs. Hazelcast vs. IBM Db2 Event Store

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

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonDataFS  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 FlinkAll data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.A widely adopted in-memory data gridDistributed Event Store optimized for Internet of Things use cases
Primary database modelTime Series DBMSObject oriented DBMSKey-value storeEvent Store
Time Series DBMS
Secondary database modelsGraph DBMSDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#159  Overall
#14  Time Series DBMS
Score0.02
Rank#369  Overall
#18  Object oriented DBMS
Score5.72
Rank#59  Overall
#6  Key-value stores
Score0.18
Rank#315  Overall
#2  Event Stores
#26  Time Series DBMS
Websiteiotdb.apache.orgnewdatabase.comhazelcast.comwww.ibm.com/­products/­db2-event-store
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldev.mobiland.com/­Overview.xsphazelcast.org/­imdg/­docswww.ibm.com/­docs/­en/­db2-event-store
DeveloperApache Software FoundationMobiland AGHazelcastIBM
Initial release2018201820082017
Current release1.1.0, April 20231.1.263, October 20225.3.6, November 20232.0
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2; commercial licenses availablecommercial infofree developer edition available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC and C++
Server operating systemsAll OS with a Java VM (>= 1.8)WindowsAll OS with a Java VMLinux infoLinux, macOS, Windows for the developer addition
Data schemeyesClasses, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)schema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 strategyno
Secondary indexesyesnoyesno
SQL infoSupport of SQLSQL-like query languagenoSQL-like query languageyes infothrough the embedded Spark runtime
APIs and other access methodsJDBC
Native API
.NET Client API
Proprietary client DLL
WinRT client
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
.Net
C
C#
C++
VB.Net
.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 proceduresyesyes infoEvent Listeners, Executor Servicesyes
Triggersyesno, except callback-events from server when changes happenedyes infoEventsno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Proprietary Sharding systemShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyes infoReplicated MapActive-active shard replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknoyesno
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 Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDone or two-phase-commit; repeatable reads; read commitedno
Concurrency infoSupport for concurrent manipulation of datayesyesyesNo - written data is immutable
Durability infoSupport for making data persistentyesyesyesYes - 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 controlyesWindows-ProfileRole-based access controlfine grained access rights according to SQL-standard

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More resources
Apache IoTDBDataFSHazelcastIBM Db2 Event Store
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