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

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

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Editorial information provided by DB-Engines
NameCoveo  Xexclude from comparisonSadas Engine  Xexclude from comparisonSpark SQL  Xexclude from comparisonVictoriaMetrics  Xexclude from comparison
DescriptionAI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code developmentSADAS 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 fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelSearch engineRelational DBMSRelational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.28
Rank#114  Overall
#11  Search engines
Score0.00
Rank#383  Overall
#158  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score1.32
Rank#162  Overall
#14  Time Series DBMS
Websitewww.coveo.comwww.sadasengine.comspark.apache.org/­sqlvictoriametrics.com
Technical documentationdocs.coveo.comwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperCoveoSADAS s.r.l.Apache Software FoundationVictoriaMetrics
Initial release2012200620142018
Current release8.03.5.0 ( 2.13), September 2023v1.91, May 2023
License infoCommercial or Open Sourcecommercialcommercial infofree trial version availableOpen Source infoApache 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++ScalaGo
Server operating systemshostedAIX
Linux
Windows
Linux
OS X
Windows
FreeBSD
Linux
macOS
OpenBSD
Data schemehybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configurationyesyes
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 indexesyesyesno
SQL infoSupport of SQLnoyesSQL-like DML and DDL statementsno
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
Proprietary protocol
JDBC
ODBC
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languagesC#
Java
JavaScript
Python
.Net
C
C#
C++
Groovy
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnononono
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodesyeshorizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesnonenoneSynchronous 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 integrityyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnono
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'nono
User concepts infoAccess controlgranular access controls, API key management, content filtersAccess rights for users, groups and roles according to SQL-standardno

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CoveoSadas EngineSpark SQLVictoriaMetrics
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