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DBMS > Hive vs. IRONdb vs. Kinetica vs. XAP

System Properties Comparison Hive vs. IRONdb vs. Kinetica vs. XAP

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Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonIRONdb  Xexclude from comparisonKinetica  Xexclude from comparisonXAP  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 simplicityGPU-accelerated database for real-time analysis of large and streaming datasetsHigh performant in-memory data grid for mission critical applications. Insight Edge from the same company extends XAP for AI/ML support, BI and other interfaces
Primary database modelRelational DBMSTime Series DBMSRelational DBMSDocument store
Key-value store infoValues are user defined objects
Secondary database modelsObject oriented DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score83.53
Rank#14  Overall
#9  Relational DBMS
Score0.06
Rank#305  Overall
#26  Time Series DBMS
Score0.59
Rank#198  Overall
#95  Relational DBMS
Score0.81
Rank#171  Overall
#27  Document stores
#30  Key-value stores
Websitehive.apache.orgwww.irondb.iowww.kinetica.comwww.gigaspaces.com/­products/­xap
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homewww.irondb.io/­docswww.kinetica.com/­docsdocs.gigaspaces.com/­latest/­landing.html
DeveloperApache Software Foundation infoinitially developed by FacebookCirconus LLC.KineticaGigaspaces Technologies
Initial release2012201720122000
Current release3.1.2, August 2019V0.10.20, January 20186.014.5.0, June 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialOpen Source infoApache Version 2; Commercial licenses available
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 languageJavaC and C++C, C++Java, C++, .Net
Server operating systemsAll OS with a Java VMLinuxLinuxLinux
macOS
Solaris
Windows
Data schemeyesschema-freeyesschema-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.nonono infoXML can be used for describing objects metadata
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query language (Circonus Analytics Query Language: CAQL)SQL-like DML and DDL statementsSQL-like query language and DML statements
APIs and other access methodsJDBC
ODBC
Thrift
HTTP APIJDBC
ODBC
RESTful HTTP API
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
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
C++
Java
JavaScript (Node.js)
Python
.Net
C++
Java
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes, in Luauser defined functionsyes
Triggersnonoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infoEvent Listeners
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodeShardingSharding infoHash based
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorconfigurable replication factor, datacenter awareMaster-slave replicationMaster-master replication infosynchronous or asynchronous
Master-slave replication infosynchronous or asynchronous
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonoyes infoMap-Reduce pattern can be built with XAP task executors
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency per node, eventual consistency across nodesImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANY
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID
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.noyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlAccess rights for users, groups and rolesnoAccess rights for users and roles on table levelRole-based access control
More information provided by the system vendor
HiveIRONdbKineticaXAP
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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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.
» more

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More resources
HiveIRONdbKineticaXAP
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