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DBMS > Spark SQL vs. Trafodion vs. VictoriaMetrics vs. YTsaurus

System Properties Comparison Spark SQL vs. Trafodion vs. VictoriaMetrics vs. YTsaurus

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Editorial information provided by DB-Engines
NameSpark SQL  Xexclude from comparisonTrafodion  Xexclude from comparisonVictoriaMetrics  Xexclude from comparisonYTsaurus  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 processingTransactional SQL-on-Hadoop DBMSA fast, cost-effective and scalable Time Series DBMS and monitoring solutionYTsaurus is an open source platform for distributed storage and processing.
Primary database modelRelational DBMSRelational DBMSTime Series DBMSDocument store
Key-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score1.32
Rank#162  Overall
#14  Time Series DBMS
Score0.11
Rank#340  Overall
#45  Document stores
#50  Key-value stores
Websitespark.apache.org/­sqltrafodion.apache.orgvictoriametrics.comytsaurus.tech
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmltrafodion.apache.org/­documentation.htmldocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
ytsaurus.tech/­docs/­en
DeveloperApache Software FoundationApache Software Foundation, originally developed by HPVictoriaMetricsYandex
Initial release2014201420182023
Current release3.5.0 ( 2.13), September 20232.3.0, February 2019v1.91, May 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache 2.0Open Source infoApache Version 2.0Open Source infoApache License, Version 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageScalaC++, JavaGoC++
Server operating systemsLinux
OS X
Windows
LinuxFreeBSD
Linux
macOS
OpenBSD
Ubuntu
Data schemeyesyes
Typing infopredefined data types such as float or dateyesyesyes
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 indexesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesnoYQL, an SQL-based language, is supported
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
ODBC
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languagesJava
Python
R
Scala
All languages supporting JDBC/ODBC/ADO.NetC++
Go
Java
JavaScript
Python
Server-side scripts infoStored proceduresnoJava Stored Proceduresno
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CoreShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes, via HBaseSynchronous replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infovia user defined functions and HBasenoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
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.nonono
User concepts infoAccess controlnofine grained access rights according to SQL-standardAccess Control Lists

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More resources
Spark SQLTrafodionVictoriaMetricsYTsaurus
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