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DBMS > Apache IoTDB vs. GigaSpaces vs. Graph Engine vs. H2 vs. TimescaleDB

System Properties Comparison Apache IoTDB vs. GigaSpaces vs. Graph Engine vs. H2 vs. TimescaleDB

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonGigaSpaces  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonH2  Xexclude from comparisonTimescaleDB  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 distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineFull-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelTime Series DBMSDocument store
Object oriented DBMS infoValues are user defined objects
Graph DBMS
Key-value store
Relational DBMSTime Series DBMS
Secondary database modelsGraph DBMS
Search engine
Spatial DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score8.13
Rank#49  Overall
#31  Relational DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websiteiotdb.apache.orgwww.gigaspaces.comwww.graphengine.iowww.h2database.comwww.timescale.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.gigaspaces.com/­latest/­landing.htmlwww.graphengine.io/­docs/­manualwww.h2database.com/­html/­main.htmldocs.timescale.com
DeveloperApache Software FoundationGigaspaces TechnologiesMicrosoftThomas MuellerTimescale
Initial release20182000201020052017
Current release1.1.0, April 202315.5, September 20202.2.220, July 20232.13.0, November 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2; Commercial licenses availableOpen Source infoMIT LicenseOpen Source infodual-licence (Mozilla public license, Eclipse public license)Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava, C++, .Net.NET and CJavaC
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
macOS
Solaris
Windows
.NETAll OS with a Java VMLinux
OS X
Windows
Data schemeyesschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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 metadatanonoyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query languageSQL-99 for query and DML statementsnoyesyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
Native API
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
RESTful HTTP APIJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
C++
Java
Python
Scala
C#
C++
F#
Visual Basic
Java.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyesyesyesJava Stored Procedures and User-Defined Functionsuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyesyes, event driven architecturenoyesyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Shardinghorizontal partitioningnoneyes, across time and space (hash partitioning) attributes
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
With clustering: 2 database servers on different computers operate on identical copies of a databaseSource-replica replication with hot standby and reads on replicas info
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 integritynononoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesyesno
User concepts infoAccess controlyesRole-based access controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Apache IoTDBGigaSpacesGraph Engine infoformer name: TrinityH2TimescaleDB
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