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DBMS > Apache IoTDB vs. EsgynDB vs. GigaSpaces vs. MonetDB

System Properties Comparison Apache IoTDB vs. EsgynDB vs. GigaSpaces vs. MonetDB

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonEsgynDB  Xexclude from comparisonGigaSpaces  Xexclude from comparisonMonetDB  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 FlinkEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsA relational database management system that stores data in columns
Primary database modelTime Series DBMSRelational DBMSDocument store
Object oriented DBMS infoValues are user defined objects
Relational DBMS
Secondary database modelsGraph DBMS
Search engine
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score1.03
Rank#188  Overall
#32  Document stores
#6  Object oriented DBMS
Score1.72
Rank#141  Overall
#64  Relational DBMS
Websiteiotdb.apache.orgwww.esgyn.cnwww.gigaspaces.comwww.monetdb.org
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.gigaspaces.com/­latest/­landing.htmlwww.monetdb.org/­Documentation
DeveloperApache Software FoundationEsgynGigaspaces TechnologiesMonetDB BV
Initial release2018201520002004
Current release1.1.0, April 202315.5, September 2020Dec2023 (11.49), December 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2; Commercial licenses availableOpen Source infoMozilla Public License 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++, JavaJava, C++, .NetC
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxLinux
macOS
Solaris
Windows
FreeBSD
Linux
OS X
Solaris
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.nonono infoXML can be used for describing objects metadata
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query languageyesSQL-99 for query and DML statementsyes infoSQL 2003 with some extensions
APIs and other access methodsJDBC
Native API
ADO.NET
JDBC
ODBC
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
JDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
All languages supporting JDBC/ODBC/ADO.Net.Net
C++
Java
Python
Scala
C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Server-side scripts infoStored proceduresyesJava Stored Proceduresyesyes, in SQL, C, R
Triggersyesnoyes, event driven architectureyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingSharding via remote tables
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 between multi datacentersMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
none infoSource-replica replication available in experimental status
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
Immediate ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANY
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
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlyesfine grained access rights according to SQL-standardRole-based access controlfine grained access rights according to SQL-standard

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More resources
Apache IoTDBEsgynDBGigaSpacesMonetDB
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