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DBMS > Apache Hive vs. ReductStore vs. Vertica

System Properties Comparison Apache Hive vs. ReductStore vs. Vertica

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Editorial information provided by DB-Engines
NameApache Hive  Xexclude from comparisonReductStore  Xexclude from comparisonVertica infoOpenText™ Vertica™  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.Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelRelational DBMSTime Series DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score51.50
Rank#18  Overall
#12  Relational DBMS
Score0.01
Rank#379  Overall
#39  Time Series DBMS
Score9.38
Rank#42  Overall
#26  Relational DBMS
Websitehive.apache.orggithub.com/­reductstore
www.reduct.store
www.vertica.com
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homewww.reduct.store/­docsvertica.com/­documentation
DeveloperApache Software Foundation infoinitially developed by FacebookReductStore LLCOpenText infopreviously Micro Focus and Hewlett Packard
Initial release201220232005
Current release3.1.3, April 20221.9, March 202412.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoBusiness Source License 1.1commercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++, RustC++
Server operating systemsAll OS with a Java VMDocker
Linux
macOS
Windows
Linux
Data schemeyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
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 indexesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL-like DML and DDL statementsFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
ODBC
Thrift
HTTP APIADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC++
Java
PHP
Python
C++
JavaScript (Node.js)
Python
Rust
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency
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
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlAccess rights for users, groups and rolesfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

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More resources
Apache HiveReductStoreVertica infoOpenText™ Vertica™
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