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DBMS > DolphinDB vs. Spark SQL vs. TerarkDB

System Properties Comparison DolphinDB vs. Spark SQL vs. TerarkDB

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Editorial information provided by DB-Engines
NameDolphinDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTerarkDB  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.Spark SQL is a component on top of 'Spark Core' for structured data processingA key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB
Primary database modelTime Series 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
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitewww.dolphindb.comspark.apache.org/­sqlgithub.com/­bytedance/­terarkdb
Technical documentationdocs.dolphindb.cn/­en/­help200/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
DeveloperDolphinDB, IncApache Software FoundationByteDance, originally Terark
Initial release201820142016
Current releasev2.00.4, January 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infofree community version availableOpen Source infoApache 2.0commercial inforestricted open source version available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ScalaC++
Server operating systemsLinux
Windows
Linux
OS X
Windows
Data schemeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesno
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.nonono
Secondary indexesyesnono
SQL infoSupport of SQLSQL-like query languageSQL-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
JDBC
ODBC
C++ API
Java API
Supported programming languagesC#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
Java
Python
R
Scala
C++
Java
Server-side scripts infoStored proceduresyesnono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesyesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlAdministrators, Users, Groupsnono

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More resources
DolphinDBSpark SQLTerarkDB
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