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DBMS > Spark SQL vs. Tkrzw vs. Trafodion vs. YDB

System Properties Comparison Spark SQL vs. Tkrzw vs. Trafodion vs. YDB

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Editorial information provided by DB-Engines
NameSpark SQL  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparisonTrafodion  Xexclude from comparisonYDB  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionSpark 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 CabinetTransactional SQL-on-Hadoop DBMSA distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API
Primary database modelRelational DBMSKey-value storeRelational DBMSDocument store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.07
Rank#372  Overall
#57  Key-value stores
Score0.33
Rank#287  Overall
#43  Document stores
#132  Relational DBMS
Websitespark.apache.org/­sqldbmx.net/­tkrzwtrafodion.apache.orggithub.com/­ydb-platform/­ydb
ydb.tech
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmltrafodion.apache.org/­documentation.htmlydb.tech/­en/­docs
DeveloperApache Software FoundationMikio HirabayashiApache Software Foundation, originally developed by HPYandex
Initial release2014202020142019
Current release3.5.0 ( 2.13), September 20230.9.3, August 20202.3.0, February 2019
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoApache 2.0; commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaC++C++, Java
Server operating systemsLinux
OS X
Windows
Linux
macOS
LinuxLinux
Data schemeyesschema-freeyesFlexible Schema (defined schema, partial schema, schema free)
Typing infopredefined data types such as float or dateyesnoyesyes
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 indexesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyesSQL-like query language (YQL)
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
ODBC
RESTful HTTP API (DynamoDB compatible)
Supported programming languagesJava
Python
R
Scala
C++
Java
Python
Ruby
All languages supporting JDBC/ODBC/ADO.NetGo
Java
JavaScript (Node.js)
PHP
Python
Server-side scripts infoStored proceduresnonoJava Stored Proceduresno
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CorenoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnonenoneyes, via HBaseActive-passive shard replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infovia user defined functions and HBaseno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID
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.noyes infousing specific database classesnono
User concepts infoAccess controlnonofine grained access rights according to SQL-standardAccess rights defined for Yandex Cloud users

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More resources
Spark SQLTkrzw infoSuccessor of Tokyo Cabinet and Kyoto CabinetTrafodionYDB
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