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DBMS > Apache IoTDB vs. JaguarDB vs. MaxDB vs. Microsoft Azure Synapse Analytics vs. TimesTen

System Properties Comparison Apache IoTDB vs. JaguarDB vs. MaxDB vs. Microsoft Azure Synapse Analytics vs. TimesTen

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonJaguarDB  Xexclude from comparisonMaxDB infoformerly named Adabas-D  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonTimesTen  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 FlinkPerformant, highly scalable DBMS for AI and IoT applicationsA robust and reliable RDBMS optimized to run all major SAP solutionsElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerAn in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.
Primary database modelTime Series DBMSKey-value store
Vector DBMS
Relational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#159  Overall
#14  Time Series DBMS
Score0.00
Rank#385  Overall
#61  Key-value stores
#16  Vector DBMS
Score2.15
Rank#115  Overall
#55  Relational DBMS
Score18.98
Rank#31  Overall
#19  Relational DBMS
Score1.26
Rank#164  Overall
#75  Relational DBMS
Websiteiotdb.apache.orgwww.jaguardb.commaxdb.sap.comazure.microsoft.com/­services/­synapse-analyticswww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.jaguardb.com/­support.htmlmaxdb.sap.com/­documentationdocs.microsoft.com/­azure/­synapse-analyticsdocs.oracle.com/­en/­database/­other-databases/­timesten/­index.html
DeveloperApache Software FoundationDataJaguar, Inc.SAP, acquired from Software AG (Adabas-D) in 1997MicrosoftOracle infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release20182015198420161998
Current release1.1.0, April 20233.3 July 20237.9.10.12, February 2024Release 22.1
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoGPL V3.0commercial infoLimited community edition freecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++ infothe server part. Clients available in other languagesC++C++
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxAIX
HP-UX
Linux
Solaris
Windows
hostedIBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64
Data schemeyesyesyesyesyes
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.nonononono
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLSQL-like query languageA subset of ANSI SQL is implemented infobut no views, foreign keys, triggersyesyesyes
APIs and other access methodsJDBC
Native API
JDBC
ODBC
ADO.NET
JDBC
ODBC
WebDAV
ADO.NET
JDBC
ODBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
.Net
C#
Java
Perl
PHP
Python
C#
Java
PHP
C
C++
Java
Node.js
PL/SQL
Python
Server-side scripts infoStored proceduresyesnoyesTransact SQLPL/SQL
Triggersyesnoyesnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingnoneSharding, horizontal partitioningnone
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 replicationSource-replica replicationyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyesno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes
User concepts infoAccess controlyesrights management via user accountsfine grained access rights according to SQL-standardyesfine grained access rights according to SQL-standard

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More resources
Apache IoTDBJaguarDBMaxDB infoformerly named Adabas-DMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseTimesTen
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