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

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

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Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonHypertable  Xexclude from comparisonSpark SQL  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionA distributed reliable key-value storeAn open source BigTable implementation based on distributed file systems such as HadoopSpark SQL is a component on top of 'Spark Core' for structured data processingA high performance, scalable Wide Column DBMS
Primary database modelKey-value storeWide column storeRelational 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
Score0.08
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
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
spark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperHypertable Inc.Apache Software FoundationAlex Kashirin
Initial release200920142020
Current release3.4, August 20190.9.8.11, March 20163.5.0 ( 2.13), September 20230.5, April 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoGNU version 3. Commercial license availableOpen 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 languageGoC++ScalaC++
Server operating systemsFreeBSD
Linux
Windows infoexperimental
Linux
OS X
Windows infoan inofficial Windows port is available
Linux
OS X
Windows
Linux
Data schemeschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or datenonoyes
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 indexesnorestricted infoonly exact value or prefix value scansno
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsSQL-like query language
APIs and other access methodsgRPC
JSON over HTTP
C++ API
Thrift
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++
Java
Perl
PHP
Python
Ruby
Java
Python
R
Scala
C++
Server-side scripts infoStored proceduresnononono
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.selectable replication factor on file system levelnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
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 datanonono
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 controlnonono

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More resources
etcdHypertableSpark SQLSWC-DB infoSuper Wide Column Database
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