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

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

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Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonSpark SQL  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionA distributed reliable key-value storeSpark SQL is a component on top of 'Spark Core' for structured data processingA high performance, scalable Wide Column DBMSOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelKey-value storeRelational DBMSWide column storeRelational DBMS
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.03
Rank#54  Overall
#5  Key-value stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.08
Rank#364  Overall
#13  Wide column stores
Websiteetcd.io
github.com/­etcd-io/­etcd
spark.apache.org/­sqlgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
yaacomo.com
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
spark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationAlex KashirinQ2WEB GmbH
Initial release201420202009
Current release3.4, August 20193.5.0 ( 2.13), September 20230.5, April 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoGPL V3commercial
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 languageGoScalaC++
Server operating systemsFreeBSD
Linux
Windows infoexperimental
Linux
OS X
Windows
LinuxAndroid
Linux
Windows
Data schemeschema-freeyesschema-freeyes
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 indexesnonoyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsSQL-like query languageyes
APIs and other access methodsgRPC
JSON over HTTP
JDBC
ODBC
Proprietary protocol
Thrift
JDBC
ODBC
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
C++
Server-side scripts infoStored proceduresnonono
Triggersyes, watching key changesnonoyes
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CoreShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.noneSource-replica replication
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 integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID
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.nononoyes
User concepts infoAccess controlnonofine grained access rights according to SQL-standard

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More resources
etcdSpark SQLSWC-DB infoSuper Wide Column DatabaseYaacomo
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