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DBMS > DolphinDB vs. Microsoft Azure Data Explorer vs. Oracle Rdb vs. Spark SQL vs. WakandaDB

System Properties Comparison DolphinDB vs. Microsoft Azure Data Explorer vs. Oracle Rdb vs. Spark SQL vs. WakandaDB

Editorial information provided by DB-Engines
NameDolphinDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOracle Rdb  Xexclude from comparisonSpark SQL  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionDolphinDB 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.Fully managed big data interactive analytics platformSpark 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 DBMSRelational DBMS infocolumn orientedRelational DBMSRelational DBMSObject oriented DBMS
Secondary database modelsRelational DBMSDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.03
Rank#78  Overall
#6  Time Series DBMS
Score3.80
Rank#81  Overall
#43  Relational 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
Websitewww.dolphindb.comazure.microsoft.com/­services/­data-explorerwww.oracle.com/­database/­technologies/­related/­rdb.htmlspark.apache.org/­sqlwakanda.github.io
Technical documentationdocs.dolphindb.cn/­en/­help200/­index.htmldocs.microsoft.com/­en-us/­azure/­data-explorerwww.oracle.com/­database/­technologies/­related/­rdb-doc.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwakanda.github.io/­doc
DeveloperDolphinDB, IncMicrosoftOracle, originally developed by Digital Equipment Corporation (DEC)Apache Software FoundationWakanda SAS
Initial release20182019198420142012
Current releasev2.00.4, January 2022cloud service with continuous releases7.4.1.1, 20213.5.0 ( 2.13), September 20232.7.0 (April 29, 2019), April 2019
License infoCommercial or Open Sourcecommercial infofree community version availablecommercialcommercialOpen Source infoApache 2.0Open Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++ScalaC++, JavaScript
Server operating systemsLinux
Windows
hostedHP Open VMSLinux
OS X
Windows
Linux
OS X
Windows
Data schemeyesFixed schema with schema-less datatypes (dynamic)Flexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or dateyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyesyes
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.noyesnonono
Secondary indexesyesall fields are automatically indexedyesno
SQL infoSupport of SQLSQL-like query languageKusto Query Language (KQL), SQL subsetyesSQL-like DML and DDL statementsno
APIs and other access methodsJDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Java
Python
R
Scala
JavaScript
Server-side scripts infoStored proceduresyesYes, possible languages: KQL, Python, Rnoyes
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningSharding infoImplicit feature of the cloud serviceyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.nonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnoyes, 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.yesnononono
User concepts infoAccess controlAdministrators, Users, GroupsAzure Active Directory Authenticationnoyes

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DolphinDBMicrosoft Azure Data ExplorerOracle RdbSpark SQLWakandaDB
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