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DBMS > Apache IoTDB vs. DolphinDB vs. Hive vs. JaguarDB vs. Microsoft Azure Table Storage

System Properties Comparison Apache IoTDB vs. DolphinDB vs. Hive vs. JaguarDB vs. Microsoft Azure Table Storage

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonDolphinDB  Xexclude from comparisonHive  Xexclude from comparisonJaguarDB  Xexclude from comparisonMicrosoft Azure Table Storage  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 FlinkDolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.data warehouse software for querying and managing large distributed datasets, built on HadoopPerformant, highly scalable DBMS for AI and IoT applicationsA Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelTime Series DBMSTime Series DBMSRelational DBMSKey-value store
Vector DBMS
Wide column store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score4.03
Rank#78  Overall
#6  Time Series DBMS
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score0.06
Rank#381  Overall
#59  Key-value stores
#13  Vector DBMS
Score4.04
Rank#77  Overall
#6  Wide column stores
Websiteiotdb.apache.orgwww.dolphindb.comhive.apache.orgwww.jaguardb.comazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.dolphindb.cn/­en/­help200/­index.htmlcwiki.apache.org/­confluence/­display/­Hive/­Homewww.jaguardb.com/­support.html
DeveloperApache Software FoundationDolphinDB, IncApache Software Foundation infoinitially developed by FacebookDataJaguar, Inc.Microsoft
Initial release20182018201220152012
Current release1.1.0, April 2023v2.00.4, January 20223.1.3, April 20223.3 July 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infofree community version availableOpen Source infoApache Version 2Open Source infoGPL V3.0commercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++JavaC++ infothe server part. Clients available in other languages
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
Windows
All OS with a Java VMLinuxhosted
Data schemeyesyesyesyesschema-free
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
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLSQL-like query languageSQL-like query languageSQL-like DML and DDL statementsA subset of ANSI SQL is implemented infobut no views, foreign keys, triggersno
APIs and other access methodsJDBC
Native API
JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket
JDBC
ODBC
Thrift
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
C++
Java
PHP
Python
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyesyesyes infouser defined functions and integration of map-reducenono
Triggersyesnononono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)horizontal partitioningShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesselectable replication factorMulti-source replicationyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyesyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyEventual ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesnonooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.yesyesnono
User concepts infoAccess controlyesAdministrators, Users, GroupsAccess rights for users, groups and rolesrights management via user accountsAccess rights based on private key authentication or shared access signatures

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More resources
Apache IoTDBDolphinDBHiveJaguarDBMicrosoft Azure Table Storage
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