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DBMS > Apache IoTDB vs. eXtremeDB vs. Hazelcast vs. Linter

System Properties Comparison Apache IoTDB vs. eXtremeDB vs. Hazelcast vs. Linter

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisoneXtremeDB  Xexclude from comparisonHazelcast  Xexclude from comparisonLinter  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 FlinkNatively in-memory DBMS with options for persistency, high-availability and clusteringA widely adopted in-memory data gridRDBMS for high security requirements
Primary database modelTime Series DBMSRelational DBMS
Time Series DBMS
Key-value storeRelational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.74
Rank#223  Overall
#103  Relational DBMS
#18  Time Series DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score0.09
Rank#346  Overall
#152  Relational DBMS
Websiteiotdb.apache.orgwww.mcobject.comhazelcast.comlinter.ru
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.mcobject.com/­docs/­extremedb.htmhazelcast.org/­imdg/­docs
DeveloperApache Software FoundationMcObjectHazelcastrelex.ru
Initial release2018200120081990
Current release1.1.0, April 20238.2, 20215.3.6, November 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2; commercial licenses availablecommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++JavaC and C++
Server operating systemsAll OS with a Java VM (>= 1.8)AIX
HP-UX
Linux
macOS
Solaris
Windows
All OS with a Java VMAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Data schemeyesyesschema-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.nono infosupport of XML interfaces availableyes infothe object must implement a serialization strategyno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query languageyes infowith the option: eXtremeSQLSQL-like query languageyes
APIs and other access methodsJDBC
Native API
.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
JCache
JPA
Memcached protocol
RESTful HTTP API
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
C
C#
C++
Java
Lua
Python
Scala
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
Server-side scripts infoStored proceduresyesyesyes infoEvent Listeners, Executor Servicesyes infoproprietary syntax with the possibility to convert from PL/SQL
Triggersyesyes infoby defining eventsyes infoEventsyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)horizontal partitioning / shardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasActive Replication Fabric™ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
yes infoReplicated MapSource-replica 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 AlgorithmImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDone or two-phase-commit; repeatable reads; read commitedACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyesyes
Durability infoSupport for making data persistentyesyesyesyes
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
More information provided by the system vendor
Apache IoTDBeXtremeDBHazelcastLinter
Specific characteristicseXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
» more
Competitive advantageseXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
» more
Typical application scenariosIoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
» more
Key customersSchneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more
Market metricsWith hundreds of customers and over 30 million devices/applications using the product...
» more
Licensing and pricing modelsFor server use cases, there is a simple per-server license irrespective of the number...
» more

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More resources
Apache IoTDBeXtremeDBHazelcastLinter
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