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

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

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Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonSpark SQL  Xexclude from comparisonSQream DB  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparison
DescriptionA distributed reliable key-value storeSpark SQL is a component on top of 'Spark Core' for structured data processinga GPU-based, columnar RDBMS for big data analytics workloadsA 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
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.74
Rank#224  Overall
#103  Relational DBMS
Score0.08
Rank#364  Overall
#13  Wide column stores
Websiteetcd.io
github.com/­etcd-io/­etcd
spark.apache.org/­sqlsqream.comgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
spark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.sqream.com
DeveloperApache Software FoundationSQream TechnologiesAlex Kashirin
Initial release201420172020
Current release3.4, August 20193.5.0 ( 2.13), September 20232022.1.6, December 20220.5, April 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0commercialOpen 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 languageGoScalaC++, CUDA, Haskell, Java, ScalaC++
Server operating systemsFreeBSD
Linux
Windows infoexperimental
Linux
OS X
Windows
LinuxLinux
Data schemeschema-freeyesyesschema-free
Typing infopredefined data types such as float or datenoyesyes, ANSI Standard SQL Types
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.nonono
Secondary indexesnonono
SQL infoSupport of SQLnoSQL-like DML and DDL statementsyesSQL-like query language
APIs and other access methodsgRPC
JSON over HTTP
JDBC
ODBC
.Net
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
R
Scala
C++
Java
JavaScript (Node.js)
Python
C++
Server-side scripts infoStored proceduresnonouser defined functions in Pythonno
Triggersyes, watching key changesnonono
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark Corehorizontal and vertical partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.nonenone
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 integritynonono
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.nonono
User concepts infoAccess controlnono

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More resources
etcdSpark SQLSQream DBSWC-DB infoSuper Wide Column Database
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