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DBMS > DolphinDB vs. EXASOL vs. Spark SQL vs. Tkrzw

System Properties Comparison DolphinDB vs. EXASOL vs. Spark SQL vs. Tkrzw

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Editorial information provided by DB-Engines
NameDolphinDB  Xexclude from comparisonEXASOL  Xexclude from comparisonSpark SQL  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  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.High-performance, in-memory, MPP database specifically designed for in-memory analytics.Spark SQL is a component on top of 'Spark Core' for structured data processingA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelTime Series DBMSRelational DBMSRelational DBMSKey-value store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.13
Rank#80  Overall
#6  Time Series DBMS
Score1.99
Rank#124  Overall
#58  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitewww.dolphindb.comwww.exasol.comspark.apache.org/­sqldbmx.net/­tkrzw
Technical documentationdocs.dolphindb.cn/­en/­help200/­index.htmlwww.exasol.com/­resourcesspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDolphinDB, IncExasolApache Software FoundationMikio Hirabayashi
Initial release2018200020142020
Current releasev2.00.4, January 20223.5.0 ( 2.13), September 20230.9.3, August 2020
License infoCommercial or Open Sourcecommercial infofree community version availablecommercialOpen Source infoApache 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ScalaC++
Server operating systemsLinux
Windows
Linux
OS X
Windows
Linux
macOS
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.nononono
Secondary indexesyesyesno
SQL infoSupport of SQLSQL-like query languageyesSQL-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
.Net
JDBC
ODBC
WebSocket
JDBC
ODBC
Supported programming languagesC#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
Java
Lua
Python
R
Java
Python
R
Scala
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresyesuser defined functionsnono
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesyesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infoHadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDno
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.yesyesnoyes infousing specific database classes
User concepts infoAccess controlAdministrators, Users, GroupsAccess rights for users, groups and roles according to SQL-standardnono

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DolphinDBEXASOLSpark SQLTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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