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DBMS > Apache Hive vs. ReductStore vs. TimesTen

System Properties Comparison Apache Hive vs. ReductStore vs. TimesTen

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Editorial information provided by DB-Engines
NameApache Hive  Xexclude from comparisonReductStore  Xexclude from comparisonTimesTen  Xexclude from comparison
Descriptiondata warehouse software for querying and managing large distributed datasets, built on HadoopDesigned to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.An in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.
Primary database modelRelational DBMSTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score62.49
Rank#18  Overall
#12  Relational DBMS
Score0.00
Rank#381  Overall
#40  Time Series DBMS
Score1.17
Rank#167  Overall
#76  Relational DBMS
Websitehive.apache.orggithub.com/­reductstore
www.reduct.store
www.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homewww.reduct.store/­docsdocs.oracle.com/­en/­database/­other-databases/­timesten/­index.html
DeveloperApache Software Foundation infoinitially developed by FacebookReductStore LLCOracle infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release201220231998
Current release3.1.3, April 20221.9, March 2024Release 22.1
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoBusiness Source License 1.1commercial
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++, Rust
Server operating systemsAll OS with a Java VMDocker
Linux
macOS
Windows
IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64
Data schemeyesyes
Typing infopredefined data types such as float or dateyesyes
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.no
Secondary indexesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
ODBC
Thrift
HTTP APIODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC
Supported programming languagesC++
Java
PHP
Python
C++
JavaScript (Node.js)
Python
Rust
C
C++
Java
Node.js
PL/SQL
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducePL/SQL
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes
User concepts infoAccess controlAccess rights for users, groups and rolesfine grained access rights according to SQL-standard

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More resources
Apache HiveReductStoreTimesTen
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