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DBMS > etcd vs. openGauss vs. Spark SQL vs. SWC-DB

System Properties Comparison etcd vs. openGauss vs. Spark SQL vs. SWC-DB

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Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonopenGauss  Xexclude from comparisonSpark SQL  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparison
DescriptionA distributed reliable key-value storeAn enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by HuaweiSpark SQL is a component on top of 'Spark Core' for structured data processingA high performance, scalable Wide Column DBMS
Primary database modelKey-value storeRelational DBMSRelational DBMSWide column store
Secondary database modelsDocument store
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.03
Rank#54  Overall
#5  Key-value stores
Score1.06
Rank#184  Overall
#84  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.08
Rank#364  Overall
#13  Wide column stores
Websiteetcd.io
github.com/­etcd-io/­etcd
gitee.com/­opengauss
opengauss.org
spark.apache.org/­sqlgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
docs.opengauss.org/­en
gitee.com/­opengauss/­docs
spark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperHuawei and openGauss communityApache Software FoundationAlex Kashirin
Initial release201920142020
Current release3.4, August 20193.0, March 20223.5.0 ( 2.13), September 20230.5, April 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open SourceOpen Source infoApache 2.0Open Source infoGPL V3
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoC, C++, JavaScalaC++
Server operating systemsFreeBSD
Linux
Windows infoexperimental
LinuxLinux
OS X
Windows
Linux
Data schemeschema-freeyesyesschema-free
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 indexesnoyesno
SQL infoSupport of SQLnoANSI SQL 2011SQL-like DML and DDL statementsSQL-like query language
APIs and other access methodsgRPC
JSON over HTTP
JDBC
ODBC
JDBC
ODBC
Proprietary protocol
Thrift
Supported programming languages.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
C
C++
Java
Java
Python
R
Scala
C++
Server-side scripts infoStored proceduresnoyesnono
Triggersyes, watching key changesyesnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by range, list and hash)yes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Source-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno
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 persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononono
User concepts infoAccess controlnoAccess rights for users, groups and roles according to SQL-standardno

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More resources
etcdopenGaussSpark SQLSWC-DB infoSuper Wide Column Database
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