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DBMS > Hive vs. IRONdb vs. RDF4J vs. Riak TS

System Properties Comparison Hive vs. IRONdb vs. RDF4J vs. Riak TS

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Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonIRONdb  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonRiak TS  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.Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV
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
Score0.22
Rank#252  Overall
#16  Time Series DBMS
Websitehive.apache.orgwww.irondb.iordf4j.orgbasho.com/­products/­riak-ts
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homewww.irondb.io/­docsdocs.rdf4j.org
DeveloperApache Software Foundation infoinitially developed by FacebookCirconus LLC.Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.Basho Technologies
Initial release2012201720042015
Current release3.1.2, August 2019V0.10.20, January 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source
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 languageJavaC and C++JavaErlang
Server operating systemsAll OS with a Java VMLinuxLinux
OS X
Unix
Windows
Linux
OS X
Data schemeyesschema-freeyes infoRDF Schemasschema-free
Typing infopredefined data types such as float or dateyesyes infotext, numeric, histogramsyesno
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
Secondary indexesyesnoyesrestricted
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
HTTP API
Native Erlang Interface
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 infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes, in LuayesJavaScript and Erlang
Triggersnonoyesyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodenoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorconfigurable replication factor, datacenter awarenoneselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency per node, eventual consistency across nodesEventual Consistency
Foreign keys infoReferential integritynonono infolinks between datasets can be stored
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
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.no
User concepts infoAccess controlAccess rights for users, groups and rolesnonono
More information provided by the system vendor
HiveIRONdbRDF4J infoformerly known as SesameRiak TS
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 SesameRiak TS
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