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DBMS > Apache IoTDB vs. CouchDB vs. GBase vs. IBM Db2 warehouse vs. Microsoft Azure Synapse Analytics

System Properties Comparison Apache IoTDB vs. CouchDB vs. GBase vs. IBM Db2 warehouse vs. Microsoft Azure Synapse Analytics

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"  Xexclude from comparisonGBase  Xexclude from comparisonIBM Db2 warehouse infoformerly named IBM dashDB  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  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 FlinkA native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.Cloud-based data warehousing serviceElastic, large scale data warehouse service leveraging the broad eco-system of SQL Server
Primary database modelTime Series DBMSDocument storeRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS infousing the Geocouch extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score9.30
Rank#45  Overall
#7  Document stores
Score1.07
Rank#185  Overall
#86  Relational DBMS
Score1.30
Rank#164  Overall
#75  Relational DBMS
Score20.56
Rank#31  Overall
#19  Relational DBMS
Websiteiotdb.apache.orgcouchdb.apache.orgwww.gbase.cnwww.ibm.com/­products/­db2/­warehouseazure.microsoft.com/­services/­synapse-analytics
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.couchdb.org/­en/­stabledocs.microsoft.com/­azure/­synapse-analytics
DeveloperApache Software FoundationApache Software Foundation infoApache top-level project, originally developed by Damien Katz, a former Lotus Notes developerGeneral Data Technology Co., Ltd.IBMMicrosoft
Initial release20182005200420142016
Current release1.1.0, April 20233.3.3, December 2023GBase 8a, GBase 8s, GBase 8c
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache version 2commercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaErlangC, Java, PythonC++
Server operating systemsAll OS with a Java VM (>= 1.8)Android
BSD
Linux
OS X
Solaris
Windows
Linuxhostedhosted
Data schemeyesschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesnoyesyesyes
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.nonoyesno infoImport/export of XML data possibleno
Secondary indexesyesyes infovia viewsyesyesyes
SQL infoSupport of SQLSQL-like query languagenoStandard with numerous extensionsyesyes
APIs and other access methodsJDBC
Native API
RESTful HTTP/JSON APIADO.NET
C API
JDBC
ODBC
.NET Client API
JDBC
ODBC
OLE DB
ADO.NET
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk
C#Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
C#
Java
PHP
Server-side scripts infoStored proceduresyesView functions in JavaScriptuser defined functionsPL/SQL, SQL PLTransact SQL
Triggersyesyesyesyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding infoimproved architecture with release 2.0horizontal partitioning (by range, list and hash) and vertical partitioningShardingSharding, horizontal partitioning
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
Source-replica replication
yesyesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyesno 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 datanono infoatomic operations within a single document possibleACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes infostrategy: optimistic lockingyesyesyes
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.yesnoyes
User concepts infoAccess controlyesAccess rights for users can be defined per databaseyesfine grained access rights according to SQL-standardyes

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More resources
Apache IoTDBCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"GBaseIBM Db2 warehouse infoformerly named IBM dashDBMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse
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