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DBMS > BoltDB vs. OpenQM vs. Postgres-XL vs. SiteWhere

System Properties Comparison BoltDB vs. OpenQM vs. Postgres-XL vs. SiteWhere

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Editorial information provided by DB-Engines
NameBoltDB  Xexclude from comparisonOpenQM infoalso called QM  Xexclude from comparisonPostgres-XL  Xexclude from comparisonSiteWhere  Xexclude from comparison
DescriptionAn embedded key-value store for Go.QpenQM is a high-performance, self-tuning, multi-value DBMSBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresM2M integration platform for persisting/querying time series data
Primary database modelKey-value storeMultivalue DBMSRelational DBMSTime Series DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.80
Rank#215  Overall
#31  Key-value stores
Score0.34
Rank#284  Overall
#10  Multivalue DBMS
Score0.53
Rank#254  Overall
#117  Relational DBMS
Score0.06
Rank#383  Overall
#43  Time Series DBMS
Websitegithub.com/­boltdb/­boltwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-open-qmwww.postgres-xl.orggithub.com/­sitewhere/­sitewhere
Technical documentationwww.postgres-xl.org/­documentationsitewhere1.sitewhere.io/­index.html
DeveloperRocket Software, originally Martin PhillipsSiteWhere
Initial release201319932014 infosince 2012, originally named StormDB2010
Current release3.4-1210 R1, October 2018
License infoCommercial or Open SourceOpen Source infoMIT LicenseOpen Source infoGPLv2, extended commercial license availableOpen Source infoMozilla public licenseOpen Source infoCommon Public Attribution License Version 1.0
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 languageGoCJava
Server operating systemsBSD
Linux
OS X
Solaris
Windows
AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows
Linux
macOS
Linux
OS X
Windows
Data schemeschema-freeyes infowith some exceptionsyespredefined scheme
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.noyesyes infoXML type, but no XML query functionalityno
Secondary indexesnoyesyesno
SQL infoSupport of SQLnonoyes infodistributed, parallel query executionno
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HTTP REST
Supported programming languagesGo.Net
Basic
C
Java
Objective C
PHP
Python
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresnoyesuser defined functions
Triggersnoyesyes
Partitioning methods infoMethods for storing different data on different nodesnoneyeshorizontal partitioningSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyesselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDACID infoMVCCno
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 controlnoAccess rights can be defined down to the item levelfine grained access rights according to SQL-standardUsers with fine-grained authorization concept

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More resources
BoltDBOpenQM infoalso called QMPostgres-XLSiteWhere
Recent citations in the news

What I learnt from building 3 high traffic web applications on an embedded key value store.
21 February 2018, hackernoon.com

4 Instructive Postmortems on Data Downtime and Loss
1 March 2024, The Hacker News

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31 January 2022, InfoWorld

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22 April 2023, The New Stack

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14 March 2023, hackernoon.com

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9 March 2023, H2S Media

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