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DBMS > BoltDB vs. etcd vs. Spark SQL vs. Tkrzw

System Properties Comparison BoltDB vs. etcd vs. Spark SQL vs. Tkrzw

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Editorial information provided by DB-Engines
NameBoltDB  Xexclude from comparisonetcd  Xexclude from comparisonSpark SQL  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionAn embedded key-value store for Go.A distributed reliable key-value storeSpark SQL is a component on top of 'Spark Core' for structured data processingA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelKey-value storeKey-value storeRelational DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.74
Rank#220  Overall
#31  Key-value stores
Score7.25
Rank#54  Overall
#5  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitegithub.com/­boltdb/­boltetcd.io
github.com/­etcd-io/­etcd
spark.apache.org/­sqldbmx.net/­tkrzw
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
spark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationMikio Hirabayashi
Initial release201320142020
Current release3.4, August 20193.5.0 ( 2.13), September 20230.9.3, August 2020
License infoCommercial or Open SourceOpen Source infoMIT LicenseOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoApache Version 2.0
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 systemsBSD
Linux
OS X
Solaris
Windows
FreeBSD
Linux
Windows infoexperimental
Linux
OS X
Windows
Linux
macOS
Data schemeschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or datenonoyesno
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 SQLnonoSQL-like DML and DDL statementsno
APIs and other access methodsgRPC
JSON over HTTP
JDBC
ODBC
Supported programming languagesGo.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
Python
Ruby
Server-side scripts infoStored proceduresnononono
Triggersnoyes, watching key changesnono
Partitioning methods infoMethods for storing different data on different nodesnoneyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneUsing 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 systemnoneImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnono
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 infousing specific database classes
User concepts infoAccess controlnononono

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BoltDBetcdSpark SQLTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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