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DBMS > Apache IoTDB vs. FatDB vs. GigaSpaces vs. Ingres

System Properties Comparison Apache IoTDB vs. FatDB vs. GigaSpaces vs. Ingres

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonFatDB  Xexclude from comparisonGigaSpaces  Xexclude from comparisonIngres  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
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 FlinkA .NET NoSQL DBMS that can integrate with and extend SQL Server.High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsWell established RDBMS
Primary database modelTime Series DBMSDocument store
Key-value store
Document store
Object oriented DBMS infoValues are user defined objects
Relational DBMS
Secondary database modelsGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score1.03
Rank#188  Overall
#32  Document stores
#6  Object oriented DBMS
Score3.80
Rank#82  Overall
#44  Relational DBMS
Websiteiotdb.apache.orgwww.gigaspaces.comwww.actian.com/­databases/­ingres
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.gigaspaces.com/­latest/­landing.htmldocs.actian.com/­ingres
DeveloperApache Software FoundationFatCloudGigaspaces TechnologiesActian Corporation
Initial release2018201220001974 infooriginally developed at University Berkely in early 1970s
Current release1.1.0, April 202315.5, September 202011.2, May 2022
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#Java, C++, .NetC
Server operating systemsAll OS with a Java VM (>= 1.8)WindowsLinux
macOS
Solaris
Windows
AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
Data schemeyesschema-freeschema-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 infoXML can be used for describing objects metadatano infobut tools for importing/exporting data from/to XML-files available
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query languageno infoVia inetgration in SQL ServerSQL-99 for query and DML statementsyes
APIs and other access methodsJDBC
Native API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#.Net
C++
Java
Python
Scala
Server-side scripts infoStored proceduresyesyes infovia applicationsyesyes
Triggersyesyes infovia applicationsyes, event driven architectureyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneously
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasselectable replication factorMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Ingres Replicator
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyesyes 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
Eventual Consistency
Immediate Consistency
Immediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoMVCC
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.yesyesno
User concepts infoAccess controlyesno infoCan implement custom security layer via applicationsRole-based access controlfine grained access rights according to SQL-standard

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More resources
Apache IoTDBFatDBGigaSpacesIngres
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