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DBMS > Apache IoTDB vs. GigaSpaces vs. Informix vs. Linter

System Properties Comparison Apache IoTDB vs. GigaSpaces vs. Informix vs. Linter

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonGigaSpaces  Xexclude from comparisonInformix  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 FlinkHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsA secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things dataRDBMS for high security requirements
Primary database modelTime Series DBMSDocument store
Object oriented DBMS infoValues are user defined objects
Relational DBMS infoSince Version 12.10 support for JSON/BSON datatypes compatible with MongoDBRelational DBMS
Secondary database modelsGraph DBMS
Search engine
Document store
Spatial DBMS
Time Series DBMS infowith Informix TimeSeries Extension
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#159  Overall
#14  Time Series DBMS
Score0.91
Rank#197  Overall
#33  Document stores
#7  Object oriented DBMS
Score16.32
Rank#35  Overall
#21  Relational DBMS
Score0.03
Rank#368  Overall
#156  Relational DBMS
Websiteiotdb.apache.orgwww.gigaspaces.comwww.ibm.com/­products/­informixlinter.ru
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.gigaspaces.com/­latest/­landing.htmlinformix.hcldoc.com
www.ibm.com/­support/­knowledgecenter/­SSGU8G/­welcomeIfxServers.html
DeveloperApache Software FoundationGigaspaces TechnologiesIBM, HCL Technologies infoEffective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.relex.ru
Initial release2018200019841990
Current release1.1.0, April 202315.5, September 202014.10.FC5, November 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2; Commercial licenses availablecommercial infofree developer edition 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++, .NetC, C++ and JavaC and C++
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
macOS
Solaris
Windows
AIX
HP-UX
Linux
macOS
Solaris
Windows
AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyes infoSince Version 12.10 support for JSON/BSON datatypesyes
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 infoXML can be used for describing objects metadatano
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query languageSQL-99 for query and DML statementsyesyes
APIs and other access methodsJDBC
Native API
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
JDBC
JSON API infoMongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
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++
Java
Python
Scala
.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
Server-side scripts infoStored proceduresyesyesyesyes infoproprietary syntax with the possibility to convert from PL/SQL
Triggersyesyes, event driven architectureyesyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)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 replicasMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Multi-source replication
Source-replica replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyes infoMap-Reduce pattern can be built with XAP task executorsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
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
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 controlUsers with fine-grained authentication, authorization, and auditing controlsfine grained access rights according to SQL-standard

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More resources
Apache IoTDBGigaSpacesInformixLinter
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