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DBMS > Hive vs. IRONdb vs. RDF4J vs. Sqrrl

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

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Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonIRONdb  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSqrrl  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.Adaptable, secure NoSQL built on Apache Accumulo
Primary database modelRelational DBMSTime Series DBMSRDF storeDocument store
Graph DBMS
Key-value store
Wide column store
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
Score0.49
Rank#209  Overall
#31  Document stores
#17  Graph DBMS
#36  Key-value stores
#10  Wide column stores
Websitehive.apache.orgwww.irondb.iordf4j.orgsqrrl.com
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.Amazon infooriginally Sqrrl Data, Inc.
Initial release2012201720042012
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.commercial
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++JavaJava
Server operating systemsAll OS with a Java VMLinuxLinux
OS X
Unix
Windows
Linux
Data schemeyesschema-freeyes infoRDF Schemasschema-free
Typing infopredefined data types such as float or dateyesyes infotext, numeric, histogramsyesyes
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.no
Secondary indexesyesnoyesyes
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
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
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
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
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 nodenoneSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorconfigurable replication factor, datacenter awarenoneselectable replication factor infomaking use of Hadoop
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 nodesImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID infoIsolation support depends on the API usedAtomic updates per row, document, or graph entity
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 rolesnonoCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)
More information provided by the system vendor
HiveIRONdbRDF4J infoformerly known as SesameSqrrl
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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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 SesameSqrrl
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