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DBMS > EXASOL vs. GRAKN.AI vs. Hive vs. IRONdb

System Properties Comparison EXASOL vs. GRAKN.AI vs. Hive vs. IRONdb

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Editorial information provided by DB-Engines
NameEXASOL  Xexclude from comparisonGRAKN.AI  Xexclude from comparisonHive  Xexclude from comparisonIRONdb  Xexclude from comparison
DescriptionHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Grakn is a distributed, hyper-relational database for managing complex data that serves as a knowledge base for cognitive/AI systems.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 simplicity
Primary database modelRelational DBMSGraph DBMS
Relational DBMS infoOften described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.
Relational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.89
Rank#89  Overall
#44  Relational DBMS
Score0.27
Rank#249  Overall
#19  Graph DBMS
#116  Relational DBMS
Score83.53
Rank#14  Overall
#9  Relational DBMS
Score0.06
Rank#305  Overall
#26  Time Series DBMS
Websitewww.exasol.com/­en/­productsgrakn.aihive.apache.orgwww.irondb.io
Technical documentationwww.exasol.com/­en/­community/­resourcesdev.grakn.ai/­docscwiki.apache.org/­confluence/­display/­Hive/­Homewww.irondb.io/­docs
DeveloperExasolGrakn Labs LtdApache Software Foundation infoinitially developed by FacebookCirconus LLC.
Initial release2000201620122017
Current release1.6.2, January 20203.1.2, August 2019V0.10.20, January 2018
License infoCommercial or Open SourcecommercialOpen Source infoGPL Version 3, commercial licenses availableOpen Source infoApache Version 2commercial
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 languageJavaJavaC and C++
Server operating systemsLinux
OS X
Windows
All OS with a Java VMLinux
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyes infotext, numeric, histograms
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.nonono
Secondary indexesyesyesyesno
SQL infoSupport of SQLyesnoSQL-like DML and DDL statementsSQL-like query language (Circonus Analytics Query Language: CAQL)
APIs and other access methods.Net
JDBC
ODBC
WebSocket
console (shell)
gRPC protocol
Workbase (visualisation software)
JDBC
ODBC
Thrift
HTTP API
Supported programming languagesJava
Lua
Python
R
All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala
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
Server-side scripts infoStored proceduresuser defined functionsnoyes infouser defined functions and integration of map-reduceyes, in Lua
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoby using CassandraShardingAutomatic, metric affinity per node
Replication methods infoMethods for redundantly storing data on multiple nodesMaster-master replication infoby using Cassandraselectable replication factorconfigurable replication factor, datacenter aware
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoHadoop integrationyes infoby using Apache Kafka and Apache Zookeeperyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyImmediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integrityyesno infosubstituted by the relationship featurenono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
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-standardyes infoat REST API level; other APIs in progressAccess rights for users, groups and rolesno
More information provided by the system vendor
EXASOLGRAKN.AIHiveIRONdb
Specific characteristicsGrakn is the knowledge graph to organise complex networks of data and making it queryable,...
» more
IRONdb is a highly available, distributed Time Series Database. It can support dozens...
» more
Competitive advantagesExpressive and flexible data model: The meta-schema of Grakn allows for modelling...
» more
Unmatched Scalability IRONdb is unique among TSDBs in that it does not use a consensus...
» more
Typical application scenariosLife sciences : Grakn makes working with biological data much easier and accelerates...
» more
Real 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 modelsAGPL and Commercial . The commercial license is priced based on cluster resources...
» more
IRONdb 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
EXASOLGRAKN.AIHiveIRONdb
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