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DBMS > 4D vs. Apache IoTDB vs. H2 vs. Microsoft Azure Synapse Analytics vs. RDFox

System Properties Comparison 4D vs. Apache IoTDB vs. H2 vs. Microsoft Azure Synapse Analytics vs. RDFox

Editorial information provided by DB-Engines
Name4D infoformer name: 4th Dimension  Xexclude from comparisonApache IoTDB  Xexclude from comparisonH2  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonRDFox  Xexclude from comparison
DescriptionApplication development environment with integrated database management systemAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkFull-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.Elastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerHigh performance knowledge graph and semantic reasoning engine
Primary database modelRelational DBMSTime Series DBMSRelational DBMSRelational DBMSGraph DBMS
RDF store
Secondary database modelsSpatial DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.47
Rank#110  Overall
#54  Relational DBMS
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score8.33
Rank#46  Overall
#30  Relational DBMS
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score0.29
Rank#300  Overall
#24  Graph DBMS
#13  RDF stores
Websitewww.4d.comiotdb.apache.orgwww.h2database.comazure.microsoft.com/­services/­synapse-analyticswww.oxfordsemantic.tech
Technical documentationdeveloper.4d.comiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.h2database.com/­html/­main.htmldocs.microsoft.com/­azure/­synapse-analyticsdocs.oxfordsemantic.tech
Developer4D, IncApache Software FoundationThomas MuellerMicrosoftOxford Semantic Technologies
Initial release19842018200520162017
Current releasev20, April 20231.1.0, April 20232.2.220, July 20236.0, Septermber 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infodual-licence (Mozilla public license, Eclipse public license)commercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC++C++
Server operating systemsOS X
Windows
All OS with a Java VM (>= 1.8)All OS with a Java VMhostedLinux
macOS
Windows
Data schemeyesyesyesyesyes infoRDF schemas
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.yesnonono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyes infoclose to SQL 92SQL-like query languageyesyesno
APIs and other access methodsODBC
RESTful HTTP API infoby using 4D Mobile
SOAP webservices
JDBC
Native API
JDBC
ODBC
ADO.NET
JDBC
ODBC
RESTful HTTP API
SPARQL 1.1
Supported programming languages4D proprietary IDE
PHP
C
C#
C++
Go
Java
Python
Scala
JavaC#
Java
PHP
C
Java
Server-side scripts infoStored proceduresyesyesJava Stored Procedures and User-Defined FunctionsTransact SQL
Triggersyesyesyesno
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning (by time range) + vertical partitioning (by deviceId)noneSharding, horizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasWith clustering: 2 database servers on different computers operate on identical copies of a databaseyesreplication via a shared file system
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoIntegration with Hadoop and Sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate ConsistencyImmediate Consistency in stand-alone mode, Eventual Consistency in replicated setups
Foreign keys infoReferential integrityyesnoyesno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraints
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes
User concepts infoAccess controlUsers and groupsyesfine grained access rights according to SQL-standardyesRoles, resources, and access types

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4D infoformer name: 4th DimensionApache IoTDBH2Microsoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseRDFox
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