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DBMS > HBase vs. IRONdb vs. RDF4J vs. Snowflake

System Properties Comparison HBase vs. IRONdb vs. RDF4J vs. Snowflake

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Editorial information provided by DB-Engines
NameHBase  Xexclude from comparisonIRONdb  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSnowflake  Xexclude from comparison
DescriptionWide-column store based on Apache Hadoop and on concepts of BigTableA 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.Cloud-based data warehousing service for structured and semi-structured data
Primary database modelWide column storeTime Series DBMSRDF storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score49.11
Rank#22  Overall
#2  Wide column stores
Score0.06
Rank#317  Overall
#28  Time Series DBMS
Score0.50
Rank#220  Overall
#9  RDF stores
Score2.59
Rank#107  Overall
#53  Relational DBMS
Websitehbase.apache.orgwww.irondb.iordf4j.orgwww.snowflake.com
Technical documentationhbase.apache.orgwww.irondb.io/­docsrdf4j.org/­documentationdocs.snowflake.net/­manuals/­index.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by PowersetCirconus LLC.Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.Snowflake Computing Inc.
Initial release2008201720042014
Current release2.2.0, June 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 servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++Java
Server operating systemsLinux
Unix
Windows infousing Cygwin
LinuxLinux
OS X
Unix
Windows
hosted
Data schemeschema-free, schema definition possibleschema-freeyes infoRDF Schemasyes infosupport of semi-structured data formats (JSON, XML, Avro)
Typing infopredefined data types such as float or dateoptions to bring your own types, AVROyes 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.nonoyes
Secondary indexesnonoyes
SQL infoSupport of SQLnoSQL-like query language (Circonus Analytics Query Language: CAQL)noyes
APIs and other access methodsJava API
RESTful HTTP API
Thrift
HTTP APIJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
CLI Client
JDBC
ODBC
Supported programming languagesC
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
Java
PHP
Python
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyes infoCoprocessors in Javayes, in Luayesuser defined functions
Triggersyesnoyesno infosimilar concept for controling cloud resources
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodenoneyes
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
configurable replication factor, datacenter awarenoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate consistency per node, eventual consistency across nodesImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataSingle row ACID (across millions of columns)noACID infoIsolation support depends on the API usedACID
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.yesnono
User concepts infoAccess controlAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACnonoUsers with fine-grained authorization concept, user roles and pluggable authentication
More information provided by the system vendor
HBaseIRONdbRDF4J infoformerly known as SesameSnowflake
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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More resources
HBaseIRONdbRDF4J infoformerly known as SesameSnowflake
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