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DBMS > EXASOL vs. Hive vs. IRONdb vs. RDF4J vs. Teradata Aster

System Properties Comparison EXASOL vs. Hive vs. IRONdb vs. RDF4J vs. Teradata Aster

Editorial information provided by DB-Engines
NameEXASOL  Xexclude from comparisonHive  Xexclude from comparisonIRONdb  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonTeradata Aster  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.data 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.Platform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMSRelational DBMSTime Series DBMSRDF storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.99
Rank#124  Overall
#58  Relational DBMS
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Websitewww.exasol.comhive.apache.orgwww.circonus.com/solutions/time-series-database/rdf4j.org
Technical documentationwww.exasol.com/­resourcescwiki.apache.org/­confluence/­display/­Hive/­Homedocs.circonus.com/irondb/category/getting-startedrdf4j.org/­documentation
DeveloperExasolApache Software Foundation infoinitially developed by FacebookCirconus LLC.Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.Teradata
Initial release20002012201720042005
Current release3.1.3, April 2022V0.10.20, January 2018
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercialOpen Source infoEclipse Distribution License (EDL), v1.0.commercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++Java
Server operating systemsAll OS with a Java VMLinuxLinux
OS X
Unix
Windows
Linux
Data schemeyesyesschema-freeyes infoRDF SchemasFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyesyesyes 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 infoin Aster File Store
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsSQL-like query language (Circonus Analytics Query Language: CAQL)noyes
APIs and other access methods.Net
JDBC
ODBC
WebSocket
JDBC
ODBC
Thrift
HTTP APIJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesJava
Lua
Python
R
C++
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
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresuser defined functionsyes infouser defined functions and integration of map-reduceyes, in LuayesR packages
Triggersyesnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingAutomatic, metric affinity per nodenoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorconfigurable replication factor, datacenter awarenoneyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoHadoop integrationyes infoquery execution via MapReducenonoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate consistency per node, eventual consistency across nodesImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID infoIsolation support depends on the API usedACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes 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 rights for users, groups and roles according to SQL-standardAccess rights for users, groups and rolesnonofine grained access rights according to SQL-standard

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More resources
EXASOLHiveIRONdbRDF4J infoformerly known as SesameTeradata Aster
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