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DBMS > Prometheus vs. Quasardb vs. Spark SQL vs. Tkrzw

System Properties Comparison Prometheus vs. Quasardb vs. Spark SQL vs. Tkrzw

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Editorial information provided by DB-Engines
NamePrometheus  Xexclude from comparisonQuasardb  Xexclude from comparisonSpark SQL  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionOpen-source Time Series DBMS and monitoring systemDistributed, high-performance timeseries databaseSpark 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 DBMSTime Series DBMSRelational DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score8.42
Rank#47  Overall
#2  Time Series DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websiteprometheus.ioquasar.aispark.apache.org/­sqldbmx.net/­tkrzw
Technical documentationprometheus.io/­docsdoc.quasar.ai/­masterspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperquasardbApache Software FoundationMikio Hirabayashi
Initial release2015200920142020
Current release3.14.1, January 20243.5.0 ( 2.13), September 20230.9.3, August 2020
License infoCommercial or Open SourceOpen Source infoApache 2.0commercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen 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 languageGoC++ScalaC++
Server operating systemsLinux
Windows
BSD
Linux
OS X
Windows
Linux
OS X
Windows
Linux
macOS
Data schemeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateNumeric data onlyyes infointeger and binaryyesno
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.no infoImport of XML data possiblenonono
Secondary indexesnoyes infowith tagsno
SQL infoSupport of SQLnoSQL-like query languageSQL-like DML and DDL statementsno
APIs and other access methodsRESTful HTTP/JSON APIHTTP APIJDBC
ODBC
Supported programming languages.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Java
Python
R
Scala
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresnononono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoconsistent hashingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoby FederationSource-replica replication with selectable replication factornonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnowith Hadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoby using LevelDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoTransient modenoyes infousing specific database classes
User concepts infoAccess controlnoCryptographically strong user authentication and audit trailnono

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PrometheusQuasardbSpark SQLTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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