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DBMS > Hive vs. IRONdb vs. Kinetica vs. Microsoft Access vs. NuoDB

System Properties Comparison Hive vs. IRONdb vs. Kinetica vs. Microsoft Access vs. NuoDB

Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonIRONdb  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonNuoDB  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
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 simplicityFully vectorized database across both GPUs and CPUsMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)NuoDB is a webscale distributed database that supports SQL and ACID transactions
Primary database modelRelational DBMSTime Series DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score64.82
Rank#18  Overall
#12  Relational DBMS
Score0.74
Rank#229  Overall
#105  Relational DBMS
Score107.93
Rank#11  Overall
#8  Relational DBMS
Score0.94
Rank#207  Overall
#96  Relational DBMS
Websitehive.apache.orgwww.circonus.com/solutions/time-series-database/www.kinetica.comwww.microsoft.com/­en-us/­microsoft-365/­accesswww.3ds.com/­nuodb-distributed-sql-database
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.circonus.com/irondb/category/getting-starteddocs.kinetica.comdeveloper.microsoft.com/­en-us/­accessdoc.nuodb.com
DeveloperApache Software Foundation infoinitially developed by FacebookCirconus LLC.KineticaMicrosoftDassault Systèmes infooriginally NuoDB, Inc.
Initial release20122017201219922013
Current release3.1.3, April 2022V0.10.20, January 20187.1, August 20211902 (16.0.11328.20222), March 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialcommercial infoBundled with Microsoft Officecommercial infolimited edition free
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC and C++C, C++C++C++
Server operating systemsAll OS with a Java VMLinuxLinuxWindows infoNot a real database server, but making use of DLLshosted infoAmazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows
Data schemeyesschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyes infotext, numeric, histogramsyesyesyes
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 indexesyesnoyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query language (Circonus Analytics Query Language: CAQL)SQL-like DML and DDL statementsyes infobut not compliant to any SQL standardyes
APIs and other access methodsJDBC
ODBC
Thrift
HTTP APIJDBC
ODBC
RESTful HTTP API
ADO.NET
DAO
ODBC
OLE DB
ADO.NET
JDBC
ODBC
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
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
.Net
C
C++
Go
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes, in Luauser defined functionsyes infosince Access 2010 using the ACE-engineJava, SQL
Triggersnonoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infosince Access 2010 using the ACE-engineyes
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodeShardingnonedata is dynamically stored/cached on the nodes where it is read/written
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorconfigurable replication factor, datacenter awareSource-replica replicationnoneyes infoManaged transparently by NuoDB
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenononono
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
Foreign keys infoReferential integritynonoyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID infobut no files for transaction loggingACID infotunable commit protocol
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes infoMVCC
Durability infoSupport for making data persistentyesyesyesyes infobut no files for transaction loggingyes
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 infoTemporary table
User concepts infoAccess controlAccess rights for users, groups and rolesnoAccess rights for users and roles on table levelno infoa simple user-level security was built in till version Access 2003Standard SQL roles/ privileges, Administrative Users

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More resources
HiveIRONdbKineticaMicrosoft AccessNuoDB
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