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DBMS > Sadas Engine vs. Spark SQL vs. TerarkDB vs. VictoriaMetrics

System Properties Comparison Sadas Engine vs. Spark SQL vs. TerarkDB vs. VictoriaMetrics

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Editorial information provided by DB-Engines
NameSadas Engine  Xexclude from comparisonSpark SQL  Xexclude from comparisonTerarkDB  Xexclude from comparisonVictoriaMetrics  Xexclude from comparison
DescriptionSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsSpark SQL is a component on top of 'Spark Core' for structured data processingA key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDBA fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelRelational DBMSRelational DBMSKey-value storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.03
Rank#379  Overall
#156  Relational DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Score0.04
Rank#377  Overall
#58  Key-value stores
Score1.42
Rank#161  Overall
#14  Time Series DBMS
Websitewww.sadasengine.comspark.apache.org/­sqlgithub.com/­bytedance/­terarkdbvictoriametrics.com
Technical documentationwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKcdocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperSADAS s.r.l.Apache Software FoundationByteDance, originally TerarkVictoriaMetrics
Initial release2006201420162018
Current release8.03.5.0 ( 2.13), September 2023v1.91, May 2023
License infoCommercial or Open Sourcecommercial infofree trial version availableOpen Source infoApache 2.0commercial inforestricted open source version availableOpen 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 languageC++ScalaC++Go
Server operating systemsAIX
Linux
Windows
Linux
OS X
Windows
FreeBSD
Linux
macOS
OpenBSD
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.nononono
Secondary indexesyesnono
SQL infoSupport of SQLyesSQL-like DML and DDL statementsnono
APIs and other access methodsJDBC
ODBC
Proprietary protocol
JDBC
ODBC
C++ API
Java API
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languages.Net
C
C#
C++
Groovy
Java
PHP
Python
Java
Python
R
Scala
C++
Java
Server-side scripts infoStored proceduresnononono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesnonenonenoneSynchronous replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
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.yes infomanaged by 'Learn by Usage'noyesno
User concepts infoAccess controlAccess rights for users, groups and roles according to SQL-standardnono

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More resources
Sadas EngineSpark SQLTerarkDBVictoriaMetrics
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