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DBMS > Apache IoTDB vs. DataFS vs. GigaSpaces vs. TimesTen

System Properties Comparison Apache IoTDB vs. DataFS vs. GigaSpaces vs. TimesTen

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NameApache IoTDB  Xexclude from comparisonDataFS  Xexclude from comparisonGigaSpaces  Xexclude from comparisonTimesTen  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.High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsAn in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.
Primary database modelTime Series DBMSObject oriented DBMSDocument store
Object oriented DBMS infoValues are user defined objects
Relational DBMS
Secondary database modelsGraph DBMSGraph DBMS
Search engine
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
Score0.91
Rank#197  Overall
#33  Document stores
#7  Object oriented DBMS
Score1.26
Rank#164  Overall
#75  Relational DBMS
Websiteiotdb.apache.orgnewdatabase.comwww.gigaspaces.comwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldev.mobiland.com/­Overview.xspdocs.gigaspaces.com/­latest/­landing.htmldocs.oracle.com/­en/­database/­other-databases/­timesten/­index.html
DeveloperApache Software FoundationMobiland AGGigaspaces TechnologiesOracle infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release2018201820001998
Current release1.1.0, April 20231.1.263, October 202215.5, September 2020Release 22.1
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 languageJavaJava, C++, .Net
Server operating systemsAll OS with a Java VM (>= 1.8)WindowsLinux
macOS
Solaris
Windows
IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64
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.nonono infoXML can be used for describing objects metadatano
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL-like query languagenoSQL-99 for query and DML statementsyes
APIs and other access methodsJDBC
Native API
.NET Client API
Proprietary client DLL
WinRT client
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
C
C#
C++
VB.Net
.Net
C++
Java
Python
Scala
C
C++
Java
Node.js
PL/SQL
Python
Server-side scripts infoStored proceduresyesyesPL/SQL
Triggersyesno, except callback-events from server when changes happenedyes, event driven architectureno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Proprietary Sharding systemShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknoyes infoMap-Reduce pattern can be built with XAP task executorsno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby means of logfiles and checkpoints
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 IoTDBDataFSGigaSpacesTimesTen
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