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DBMS > Apache IoTDB vs. IBM Db2 warehouse vs. Microsoft Azure Synapse Analytics vs. Riak KV

System Properties Comparison Apache IoTDB vs. IBM Db2 warehouse vs. Microsoft Azure Synapse Analytics vs. Riak KV

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonIBM Db2 warehouse infoformerly named IBM dashDB  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonRiak KV  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 FlinkCloud-based data warehousing serviceElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerDistributed, fault tolerant key-value store
Primary database modelTime Series DBMSRelational DBMSRelational DBMSKey-value store infowith links between data sets and object tags for the creation of secondary indexes
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score1.30
Rank#164  Overall
#75  Relational DBMS
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score4.10
Rank#82  Overall
#9  Key-value stores
Websiteiotdb.apache.orgwww.ibm.com/­products/­db2/­warehouseazure.microsoft.com/­services/­synapse-analytics
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.microsoft.com/­azure/­synapse-analyticswww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperApache Software FoundationIBMMicrosoftOpenSource, formerly Basho Technologies
Initial release2018201420162009
Current release1.1.0, April 20233.2.0, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoApache version 2, commercial enterprise edition
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++Erlang
Server operating systemsAll OS with a Java VM (>= 1.8)hostedhostedLinux
OS X
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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 infoImport/export of XML data possiblenono
Secondary indexesyesyesyesrestricted
SQL infoSupport of SQLSQL-like query languageyesyesno
APIs and other access methodsJDBC
Native API
.NET Client API
JDBC
ODBC
OLE DB
ADO.NET
JDBC
ODBC
HTTP API
Native Erlang Interface
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
C#
Java
PHP
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Server-side scripts infoStored proceduresyesPL/SQL, SQL PLTransact SQLErlang
Triggersyesyesnoyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingSharding, horizontal partitioningSharding infono "single point of failure"
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesyesselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsno infolinks between data sets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDno
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.yesyes
User concepts infoAccess controlyesfine grained access rights according to SQL-standardyesyes, using Riak Security

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More resources
Apache IoTDBIBM Db2 warehouse infoformerly named IBM dashDBMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseRiak KV
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