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DBMS > Apache IoTDB vs. GBase vs. Hazelcast vs. IBM Db2 Event Store vs. PouchDB

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

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonGBase  Xexclude from comparisonHazelcast  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonPouchDB  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 FlinkAn analytical database for business intelligence with large customers in China.A widely adopted in-memory data gridDistributed Event Store optimized for Internet of Things use casesJavaScript DBMS with an API inspired by CouchDB
Primary database modelTime Series DBMSRelational DBMSKey-value storeEvent Store
Time Series DBMS
Document store
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
Score1.04
Rank#190  Overall
#88  Relational DBMS
Score6.87
Rank#55  Overall
#6  Key-value stores
Score0.23
Rank#316  Overall
#2  Event Stores
#28  Time Series DBMS
Score2.35
Rank#116  Overall
#22  Document stores
Websiteiotdb.apache.orgwww.gbase.cnhazelcast.comwww.ibm.com/­products/­db2-event-storepouchdb.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlhazelcast.org/­imdg/­docswww.ibm.com/­docs/­en/­db2-event-storepouchdb.com/­guides
DeveloperApache Software FoundationHazelcastIBMApache Software Foundation
Initial release2018200820172012
Current release1.1.0, April 2023GBase 8a5.3.6, November 20232.07.1.1, June 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2; commercial licenses availablecommercial infofree developer edition availableOpen Source
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC and C++JavaScript
Server operating systemsAll OS with a Java VM (>= 1.8)All OS with a Java VMLinux infoLinux, macOS, Windows for the developer additionserver-less, requires a JavaScript environment (browser, Node.js)
Data schemeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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 indexesyesyesnoyes infovia views
SQL infoSupport of SQLSQL-like query languageSQL-like query languageyes infothrough the embedded Spark runtimeno
APIs and other access methodsJDBC
Native API
JCache
JPA
Memcached protocol
RESTful HTTP API
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
HTTP REST infoonly for PouchDB Server
JavaScript API
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
JavaScript
Server-side scripts infoStored proceduresyesyes infoEvent Listeners, Executor ServicesyesView functions in JavaScript
Triggersyesyes infoEventsnoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingSharding infowith a proxy-based framework, named couchdb-lounge
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 replicationMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyesnoyes
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 immutable
Durability infoSupport for making data persistentyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyes infoby using IndexedDB, WebSQL or LevelDB as backend
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesyes
User concepts infoAccess controlyesRole-based access controlfine grained access rights according to SQL-standardno

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More resources
Apache IoTDBGBaseHazelcastIBM Db2 Event StorePouchDB
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