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DBMS > Hive vs. IRONdb vs. RDF4J vs. RRDtool

System Properties Comparison Hive vs. IRONdb vs. RDF4J vs. RRDtool

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Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonIRONdb  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonRRDtool  Xexclude from comparison
Descriptiondata warehouse software for querying and managing large distributed datasets, built on HadoopA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.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.
Primary database modelRelational DBMSTime Series DBMSRDF storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score84.22
Rank#14  Overall
#9  Relational DBMS
Score0.05
Rank#328  Overall
#27  Time Series DBMS
Score0.38
Rank#223  Overall
#10  RDF stores
Score2.90
Rank#91  Overall
#5  Time Series DBMS
Websitehive.apache.orgwww.irondb.iordf4j.orgoss.oetiker.ch/­rrdtool
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homewww.irondb.io/­docsdocs.rdf4j.orgoss.oetiker.ch/­rrdtool/­doc
DeveloperApache Software Foundation infoinitially developed by FacebookCirconus LLC.Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.Tobias Oetiker
Initial release2012201720041999
Current release3.1.2, August 2019V0.10.20, January 20181.7.2, May 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoGPL V2 and FLOSS
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++JavaC infoImplementations in Java (e.g. RRD4J) and C# available
Server operating systemsAll OS with a Java VMLinuxLinux
OS X
Unix
Windows
HP-UX
Linux
Data schemeyesschema-freeyes infoRDF Schemasyes
Typing infopredefined data types such as float or dateyesyes infotext, numeric, histogramsyesNumeric data only
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 possible
Secondary indexesyesnoyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query language (Circonus Analytics Query Language: CAQL)nono
APIs and other access methodsJDBC
ODBC
Thrift
HTTP APIJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
in-process shared library
Pipes
Supported programming languagesC++
Java
PHP
Python
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
Java
PHP
Python
C 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
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes, in Luayesno
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodenonenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorconfigurable replication factor, datacenter awarenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency per node, eventual consistency across nodesnone
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID infoIsolation support depends on the API usedno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoby using the rrdcached daemon
Durability infoSupport for making data persistentyesyesyes infoin-memory storage is supported as wellyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlAccess rights for users, groups and rolesnonono
More information provided by the system vendor
HiveIRONdbRDF4J infoformerly known as SesameRRDtool
Specific characteristicsIRONdb is a highly available, distributed Time Series Database. It can support dozens...
» more
Competitive advantagesUnmatched Scalability IRONdb is unique among TSDBs in that it does not use a consensus...
» more
Typical application scenariosReal Systems Monitoring Monitor your systems infrastructure in real time across thousands...
» more
Key customersIRONdb serves the needs of the world's largest Time Series Database customers. One...
» more
Market metricsOnly TSDB capable of scaling to billions of metrics. Only TSDB to scale to dozens...
» more
Licensing and pricing modelsIRONdb is licensed under a subscription model based on the number of active metrics...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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3rd partiesDremio is like magic for Hive accelerating your analytical queries up to 1,000x.
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More resources
HiveIRONdbRDF4J infoformerly known as SesameRRDtool
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