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

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

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Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonFeatureBase  Xexclude from comparisonSpark SQL  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparison
DescriptionA distributed reliable key-value storeReal-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.Spark 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 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
Score0.31
Rank#292  Overall
#135  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
www.featurebase.comspark.apache.org/­sqlgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
docs.featurebase.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperMolecula and Pilosa Open Source ContributorsApache Software FoundationAlex Kashirin
Initial release201720142020
Current release3.4, August 20192022, May 20223.5.0 ( 2.13), September 20230.5, April 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0Open Source infoGPL V3
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 languageGoGoScalaC++
Server operating systemsFreeBSD
Linux
Windows infoexperimental
Linux
macOS
Linux
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 indexesnonono
SQL infoSupport of SQLnoSQL queriesSQL-like DML and DDL statementsSQL-like query language
APIs and other access methodsgRPC
JSON over HTTP
gRPC
JDBC
Kafka Connector
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
Java
Python
Java
Python
R
Scala
C++
Server-side scripts infoStored proceduresnonono
Triggersyes, watching key changesnonono
Partitioning methods infoMethods for storing different data on different nodesShardingyes, 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.yesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes, using Linux fsyncyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnono
User concepts infoAccess controlnono

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More resources
etcdFeatureBaseSpark SQLSWC-DB infoSuper Wide Column Database
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