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DBMS > EsgynDB vs. Hive vs. IRONdb vs. RDF4J

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

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonHive  Xexclude from comparisonIRONdb  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache Trafodiondata 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.
Primary database modelRelational DBMSRelational DBMSTime Series DBMSRDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#264  Overall
#124  Relational DBMS
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
Websiteesgyn.comhive.apache.orgwww.irondb.iordf4j.org
Technical documentationesgyn.com/­developerscwiki.apache.org/­confluence/­display/­Hive/­Homewww.irondb.io/­docsdocs.rdf4j.org
DeveloperEsgynApache Software Foundation infoinitially developed by FacebookCirconus LLC.Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2015201220172004
Current release3.1.2, August 2019V0.10.20, January 2018
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercialOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaJavaC and C++Java
Server operating systemsLinuxAll OS with a Java VMLinuxLinux
OS X
Unix
Windows
Data schemeyesyesschema-freeyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyesyes infotext, numeric, histogramsyes
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 indexesyesyesnoyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsSQL-like query language (Circonus Analytics Query Language: CAQL)no
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
Thrift
HTTP APIJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC++
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
Server-side scripts infoStored proceduresJava Stored Proceduresyes infouser defined functions and integration of map-reduceyes, in Luayes
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingAutomatic, metric affinity per nodenone
Replication methods infoMethods for redundantly storing data on multiple nodesMaster-master replication between multi datacentersselectable replication factorconfigurable replication factor, datacenter awarenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoin-memory storage is supported as well
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and rolesnono
More information provided by the system vendor
EsgynDBHiveIRONdbRDF4J infoformerly known as Sesame
Specific characteristicsCapabilities for Operational/Transactional Workloads Deep Integration with HBase...
» more
IRONdb is a highly available, distributed Time Series Database. It can support dozens...
» more
Competitive advantagesEsgynDB is ideally suited to supporting Hybrid Transactional and Analytical Processing...
» more
Unmatched Scalability IRONdb is unique among TSDBs in that it does not use a consensus...
» more
Typical application scenariosIdeally suited to scenarios where high speed continuous data ingestion is required...
» more
Real Systems Monitoring Monitor your systems infrastructure in real time across thousands...
» more
Key customersEsgynDB's customers are worldwide, with several in the Global Fortune 500, including...
» more
IRONdb 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 modelsEsgynDB Enterprise Edition is the commercially supported version of Apache Trafodion...
» more
IRONdb 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
EsgynDBHiveIRONdbRDF4J infoformerly known as Sesame
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