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DBMS > Apache IoTDB vs. Apache Phoenix vs. IBM Db2 Event Store vs. IBM Db2 warehouse vs. Microsoft Azure Synapse Analytics

System Properties Comparison Apache IoTDB vs. Apache Phoenix vs. IBM Db2 Event Store vs. IBM Db2 warehouse vs. Microsoft Azure Synapse Analytics

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonApache Phoenix  Xexclude from comparisonIBM Db2 Event Store  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 scale-out RDBMS with evolutionary schema built on Apache HBaseDistributed Event Store optimized for Internet of Things use casesCloud-based data warehousing serviceElastic, large scale data warehouse service leveraging the broad eco-system of SQL Server
Primary database modelTime Series DBMSRelational DBMSEvent Store
Time Series DBMS
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score1.30
Rank#164  Overall
#75  Relational DBMS
Score20.56
Rank#31  Overall
#19  Relational DBMS
Websiteiotdb.apache.orgphoenix.apache.orgwww.ibm.com/­products/­db2-event-storewww.ibm.com/­products/­db2/­warehouseazure.microsoft.com/­services/­synapse-analytics
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlphoenix.apache.orgwww.ibm.com/­docs/­en/­db2-event-storedocs.microsoft.com/­azure/­synapse-analytics
DeveloperApache Software FoundationApache Software FoundationIBMIBMMicrosoft
Initial release20182014201720142016
Current release1.1.0, April 20235.0-HBase2, July 2018 and 4.15-HBase1, December 20192.0
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0commercial infofree developer edition availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC and C++C++
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
Unix
Windows
Linux infoLinux, macOS, Windows for the developer additionhostedhosted
Data schemeyesyes infolate-bound, schema-on-read capabilitiesyesyesyes
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.nononono infoImport/export of XML data possibleno
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLSQL-like query languageyesyes infothrough the embedded Spark runtimeyesyes
APIs and other access methodsJDBC
Native API
JDBCADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
.NET Client API
JDBC
ODBC
OLE DB
ADO.NET
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
C#
Java
PHP
Server-side scripts infoStored proceduresyesuser defined functionsyesPL/SQL, SQL PLTransact SQL
Triggersyesnonoyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingShardingSharding, 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
Active-active shard replicationyesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparkHadoop integrationnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency or Eventual ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesno 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 datanoACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesNo - written data is immutableyesyes
Durability infoSupport for making data persistentyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesyes
User concepts infoAccess controlyesAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardyes

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More resources
Apache IoTDBApache PhoenixIBM Db2 Event StoreIBM Db2 warehouse infoformerly named IBM dashDBMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse
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