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DBMS > GeoMesa vs. RRDtool vs. Spark SQL vs. Transbase vs. VictoriaMetrics

System Properties Comparison GeoMesa vs. RRDtool vs. Spark SQL vs. Transbase vs. VictoriaMetrics

Editorial information provided by DB-Engines
NameGeoMesa  Xexclude from comparisonRRDtool  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparisonVictoriaMetrics  Xexclude from comparison
DescriptionGeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database. infoThe data is stored in a circular buffer, thus the system storage footprint remains constant over time.Spark SQL is a component on top of 'Spark Core' for structured data processingA resource-optimized, high-performance, universally applicable RDBMSA fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelSpatial DBMSTime Series DBMSRelational DBMSRelational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.86
Rank#205  Overall
#4  Spatial DBMS
Score1.90
Rank#132  Overall
#11  Time Series DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.17
Rank#334  Overall
#148  Relational DBMS
Score1.23
Rank#172  Overall
#15  Time Series DBMS
Websitewww.geomesa.orgoss.oetiker.ch/­rrdtoolspark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.htmlvictoriametrics.com
Technical documentationwww.geomesa.org/­documentation/­stable/­user/­index.htmloss.oetiker.ch/­rrdtool/­docspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.htmldocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperCCRi and othersTobias OetikerApache Software FoundationTransaction Software GmbHVictoriaMetrics
Initial release20141999201419872018
Current release5.0.0, May 20241.8.0, 20223.5.0 ( 2.13), September 2023Transbase 8.3, 2022v1.91, May 2023
License infoCommercial or Open SourceOpen Source infoApache License 2.0Open Source infoGPL V2 and FLOSSOpen Source infoApache 2.0commercial infofree development licenseOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageScalaC infoImplementations in Java (e.g. RRD4J) and C# availableScalaC and C++Go
Server operating systemsHP-UX
Linux
Linux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
FreeBSD
Linux
macOS
OpenBSD
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesNumeric data onlyyesyes
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.nono infoExporting into and restoring from XML files possiblenonono
Secondary indexesyesnonoyes
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsyesno
APIs and other access methodsin-process shared library
Pipes
JDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languagesC infowith librrd library
C# infowith a different implementation of RRDTool
Java infowith a different implementation of RRDTool
JavaScript (Node.js) infowith a different implementation of RRDTool
Lua
Perl
PHP infowith a wrapper library
Python
Ruby
Java
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresnononoyesno
Triggersnononoyesno
Partitioning methods infoMethods for storing different data on different nodesdepending on storage layernoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesdepending on storage layernonenoneSource-replica replicationSynchronous replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemdepending on storage layernoneImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoyesno
Concurrency infoSupport for concurrent manipulation of datayesyes infoby using the rrdcached daemonyesyesyes
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.depending on storage layeryesnonono
User concepts infoAccess controlyes infodepending on the DBMS used for storagenonofine grained access rights according to SQL-standard

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More resources
GeoMesaRRDtoolSpark SQLTransbaseVictoriaMetrics
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