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

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

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonHazelcast  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonNSDb  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 FlinkA widely adopted in-memory data gridDistributed Event Store optimized for Internet of Things use casesScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes
Primary database modelTime Series DBMSKey-value storeEvent Store
Time Series DBMS
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
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Websiteiotdb.apache.orghazelcast.comwww.ibm.com/­products/­db2-event-storensdb.io
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlhazelcast.org/­imdg/­docswww.ibm.com/­docs/­en/­db2-event-storensdb.io/­Architecture
DeveloperApache Software FoundationHazelcastIBM
Initial release2018200820172017
Current release1.1.0, April 20235.3.6, November 20232.0
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2; commercial licenses availablecommercial infofree developer edition availableOpen Source infoApache Version 2.0
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++Java, Scala
Server operating systemsAll OS with a Java VM (>= 1.8)All OS with a Java VMLinux infoLinux, macOS, Windows for the developer additionLinux
macOS
Data schemeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes: int, bigint, decimal, string
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.noyes infothe object must implement a serialization strategynono
Secondary indexesyesyesnoall fields are automatically indexed
SQL infoSupport of SQLSQL-like query languageSQL-like query languageyes infothrough the embedded Spark runtimeSQL-like query language
APIs and other access methodsJDBC
Native API
JCache
JPA
Memcached protocol
RESTful HTTP API
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
gRPC
HTTP REST
WebSocket
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.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
Java
Scala
Server-side scripts infoStored proceduresyesyes infoEvent Listeners, Executor Servicesyesno
Triggersyesyes infoEventsno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingSharding
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 Sparkyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoone or two-phase-commit; repeatable reads; read commitednono
Concurrency infoSupport for concurrent manipulation of datayesyesNo - written data is immutableyes
Durability infoSupport for making data persistentyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageUsing Apache Lucene
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlyesRole-based access controlfine grained access rights according to SQL-standard

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More resources
Apache IoTDBHazelcastIBM Db2 Event StoreNSDb
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