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DBMS > Apache IoTDB vs. GridGain vs. Hazelcast vs. SiteWhere

System Properties Comparison Apache IoTDB vs. GridGain vs. Hazelcast vs. SiteWhere

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonGridGain  Xexclude from comparisonHazelcast  Xexclude from comparisonSiteWhere  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 FlinkGridGain is an in-memory computing platform, built on Apache IgniteA widely adopted in-memory data gridM2M integration platform for persisting/querying time series data
Primary database modelTime Series DBMSKey-value store
Relational DBMS
Key-value storeTime 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
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Score0.06
Rank#383  Overall
#43  Time Series DBMS
Websiteiotdb.apache.orgwww.gridgain.comhazelcast.comgithub.com/­sitewhere/­sitewhere
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.gridgain.com/­docs/­index.htmlhazelcast.org/­imdg/­docssitewhere1.sitewhere.io/­index.html
DeveloperApache Software FoundationGridGain Systems, Inc.HazelcastSiteWhere
Initial release2018200720082010
Current release1.1.0, April 2023GridGain 8.5.15.3.6, November 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2; commercial licenses availableOpen Source infoCommon Public Attribution License Version 1.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava, C++, .NetJavaJava
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
OS X
Solaris
Windows
All OS with a Java VMLinux
OS X
Windows
Data schemeyesyesschema-freepredefined scheme
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.noyesyes infothe object must implement a serialization strategyno
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-like query languageANSI-99 for query and DML statements, subset of DDLSQL-like query languageno
APIs and other access methodsJDBC
Native API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JCache
JPA
Memcached protocol
RESTful HTTP API
HTTP REST
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresyesyes (compute grid and cache interceptors can be used instead)yes infoEvent Listeners, Executor Services
Triggersyesyes (cache interceptors and events)yes infoEvents
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingSharding infobased on HBase
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 (replicated cache)yes infoReplicated Mapselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyes (compute grid and hadoop accelerator)yesno
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 integritynononono
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 datayesyesyesyes
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.yesyesyesno
User concepts infoAccess controlyesSecurity Hooks for custom implementationsRole-based access controlUsers with fine-grained authorization concept

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More resources
Apache IoTDBGridGainHazelcastSiteWhere
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