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DBMS > etcd vs. SiteWhere vs. Spark SQL vs. VictoriaMetrics

System Properties Comparison etcd vs. SiteWhere vs. Spark SQL vs. VictoriaMetrics

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Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonSiteWhere  Xexclude from comparisonSpark SQL  Xexclude from comparisonVictoriaMetrics  Xexclude from comparison
DescriptionA distributed reliable key-value storeM2M integration platform for persisting/querying time series dataSpark 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 modelKey-value storeTime Series DBMSRelational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.03
Rank#54  Overall
#5  Key-value stores
Score0.06
Rank#383  Overall
#43  Time Series DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score1.23
Rank#172  Overall
#15  Time Series DBMS
Websiteetcd.io
github.com/­etcd-io/­etcd
github.com/­sitewhere/­sitewherespark.apache.org/­sqlvictoriametrics.com
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
sitewhere1.sitewhere.io/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperSiteWhereApache Software FoundationVictoriaMetrics
Initial release201020142018
Current release3.4, August 20193.5.0 ( 2.13), September 2023v1.91, May 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoCommon Public Attribution License Version 1.0Open 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

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoJavaScalaGo
Server operating systemsFreeBSD
Linux
Windows infoexperimental
Linux
OS X
Windows
Linux
OS X
Windows
FreeBSD
Linux
macOS
OpenBSD
Data schemeschema-freepredefined schemeyes
Typing infopredefined data types such as float or datenoyesyes
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 indexesnonono
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsno
APIs and other access methodsgRPC
JSON over HTTP
HTTP RESTJDBC
ODBC
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languages.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
Java
Python
R
Scala
Server-side scripts infoStored proceduresnonono
Triggersyes, watching key changesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on HBaseyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.selectable replication factor infobased on HBasenoneSynchronous 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 integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononono
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.nononono
User concepts infoAccess controlnoUsers with fine-grained authorization conceptno

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More resources
etcdSiteWhereSpark SQLVictoriaMetrics
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