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DBMS > BoltDB vs. Linter vs. Netezza vs. Spark SQL vs. SWC-DB

System Properties Comparison BoltDB vs. Linter vs. Netezza vs. Spark SQL vs. SWC-DB

Editorial information provided by DB-Engines
NameBoltDB  Xexclude from comparisonLinter  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSpark SQL  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparison
DescriptionAn embedded key-value store for Go.RDBMS for high security requirementsData warehouse and analytics appliance part of IBM PureSystemsSpark 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 DBMSRelational DBMSWide column store
Secondary database modelsSpatial DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.80
Rank#215  Overall
#31  Key-value stores
Score0.12
Rank#350  Overall
#152  Relational DBMS
Score8.59
Rank#45  Overall
#29  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.08
Rank#364  Overall
#13  Wide column stores
Websitegithub.com/­boltdb/­boltlinter.ruwww.ibm.com/­products/­netezzaspark.apache.org/­sqlgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
Developerrelex.ruIBMApache Software FoundationAlex Kashirin
Initial release20131990200020142020
Current release3.5.0 ( 2.13), September 20230.5, April 2021
License infoCommercial or Open SourceOpen Source infoMIT LicensecommercialcommercialOpen Source infoApache 2.0Open Source infoGPL V3
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoC and C++ScalaC++
Server operating systemsBSD
Linux
OS X
Solaris
Windows
AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Linux infoincluded in applianceLinux
OS X
Windows
Linux
Data schemeschema-freeyesyesyesschema-free
Typing infopredefined data types such as float or datenoyesyesyes
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 indexesnoyesyesno
SQL infoSupport of SQLnoyesyesSQL-like DML and DDL statementsSQL-like query language
APIs and other access methodsADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
JDBC
ODBC
OLE DB
JDBC
ODBC
Proprietary protocol
Thrift
Supported programming languagesGoC
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
C
C++
Fortran
Java
Lua
Perl
Python
R
Java
Python
R
Scala
C++
Server-side scripts infoStored proceduresnoyes infoproprietary syntax with the possibility to convert from PL/SQLyesnono
Triggersnoyesnonono
Partitioning methods infoMethods for storing different data on different nodesnonenoneShardingyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlnofine grained access rights according to SQL-standardUsers with fine-grained authorization conceptno

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More resources
BoltDBLinterNetezza infoAlso called PureData System for Analytics by IBMSpark SQLSWC-DB infoSuper Wide Column Database
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