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DBMS > Spark SQL vs. TDSQL for MySQL vs. TerarkDB

System Properties Comparison Spark SQL vs. TDSQL for MySQL vs. TerarkDB

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Editorial information provided by DB-Engines
NameSpark SQL  Xexclude from comparisonTDSQL for MySQL  Xexclude from comparisonTerarkDB  Xexclude from comparison
DescriptionSpark SQL is a component on top of 'Spark Core' for structured data processingA high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.A 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 modelRelational DBMSRelational DBMSKey-value store
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score19.56
Rank#34  Overall
#21  Relational DBMS
Score0.85
Rank#214  Overall
#98  Relational DBMS
Score0.06
Rank#377  Overall
#57  Key-value stores
Websitespark.apache.org/­sqlwww.tencentcloud.com/­products/­dcdbgithub.com/­bytedance/­terarkdb
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.tencentcloud.com/­document/­product/­1042bytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
DeveloperApache Software FoundationTencentByteDance, originally Terark
Initial release201420132016
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercial inforestricted open source version available
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaC++
Server operating systemsLinux
OS X
Windows
hosted
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 indexesnoyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsyesno
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
C++ API
Java API
Supported programming languagesJava
Python
R
Scala
C
C#
C++
Java
PHP
Python
Ruby
C++
Java
Server-side scripts infoStored proceduresnoyesno
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CoreAutomatic shardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
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 datanoACIDno
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.nonoyes
User concepts infoAccess controlnoUsers with fine-grained authorization conceptno

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More resources
Spark SQLTDSQL for MySQLTerarkDB
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