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DBMS > LeanXcale vs. Spark SQL vs. SQream DB vs. VictoriaMetrics

System Properties Comparison LeanXcale vs. Spark SQL vs. SQream DB vs. VictoriaMetrics

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Editorial information provided by DB-Engines
NameLeanXcale  Xexclude from comparisonSpark SQL  Xexclude from comparisonSQream DB  Xexclude from comparisonVictoriaMetrics  Xexclude from comparison
DescriptionA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesSpark SQL is a component on top of 'Spark Core' for structured data processinga GPU-based, columnar RDBMS for big data analytics workloadsA fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelKey-value store
Relational DBMS
Relational DBMSRelational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.29
Rank#291  Overall
#41  Key-value stores
#132  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.70
Rank#227  Overall
#104  Relational DBMS
Score1.32
Rank#162  Overall
#14  Time Series DBMS
Websitewww.leanxcale.comspark.apache.org/­sqlsqream.comvictoriametrics.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.sqream.comdocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperLeanXcaleApache Software FoundationSQream TechnologiesVictoriaMetrics
Initial release2015201420172018
Current release3.5.0 ( 2.13), September 20232022.1.6, December 2022v1.91, May 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialOpen Source infoApache 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++, CUDA, Haskell, Java, ScalaGo
Server operating systemsLinux
OS X
Windows
LinuxFreeBSD
Linux
macOS
OpenBSD
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyes, ANSI Standard SQL Types
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.nono
Secondary indexesnono
SQL infoSupport of SQLyes infothrough Apache DerbySQL-like DML and DDL statementsyesno
APIs and other access methodsJDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
JDBC
ODBC
.Net
JDBC
ODBC
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languagesC
Java
Scala
Java
Python
R
Scala
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnouser defined functions in Pythonno
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark Corehorizontal and vertical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnonenoneSynchronous replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDno
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.yesnono
User concepts infoAccess controlno

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More resources
LeanXcaleSpark SQLSQream DBVictoriaMetrics
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