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DBMS > Apache IoTDB vs. DolphinDB vs. Oracle Rdb vs. Spark SQL vs. WakandaDB

System Properties Comparison Apache IoTDB vs. DolphinDB vs. Oracle Rdb vs. Spark SQL vs. WakandaDB

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonDolphinDB  Xexclude from comparisonOracle Rdb  Xexclude from comparisonSpark SQL  Xexclude from comparisonWakandaDB  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.Spark SQL is a component on top of 'Spark Core' for structured data processingWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelTime Series DBMSTime Series DBMSRelational DBMSRelational DBMSObject oriented DBMS
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
Score1.14
Rank#178  Overall
#80  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.10
Rank#356  Overall
#16  Object oriented DBMS
Websiteiotdb.apache.orgwww.dolphindb.comwww.oracle.com/­database/­technologies/­related/­rdb.htmlspark.apache.org/­sqlwakanda.github.io
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.dolphindb.cn/­en/­help200/­index.htmlwww.oracle.com/­database/­technologies/­related/­rdb-doc.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwakanda.github.io/­doc
DeveloperApache Software FoundationDolphinDB, IncOracle, originally developed by Digital Equipment Corporation (DEC)Apache Software FoundationWakanda SAS
Initial release20182018198420142012
Current release1.1.0, April 2023v2.00.4, January 20227.4.1.1, 20213.5.0 ( 2.13), September 20232.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infofree community version availablecommercialOpen Source infoApache 2.0Open Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++ScalaC++, JavaScript
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
Windows
HP Open VMSLinux
OS X
Windows
Linux
OS X
Windows
Data schemeyesyesFlexible Schema (defined schema, partial schema, schema free)yesyes
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 indexesyesyesyesno
SQL infoSupport of SQLSQL-like query languageSQL-like query languageyesSQL-like DML and DDL statementsno
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
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
Java
Python
R
Scala
JavaScript
Server-side scripts infoStored proceduresyesyesnoyes
Triggersyesnonoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)horizontal partitioningyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesnonenone
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
Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesyes, on a single nodenoACID
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.yesyesnonono
User concepts infoAccess controlyesAdministrators, Users, Groupsnoyes

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More resources
Apache IoTDBDolphinDBOracle RdbSpark SQLWakandaDB
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