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DBMS > Citus vs. Hive vs. Quasardb vs. Riak KV vs. Vertica

System Properties Comparison Citus vs. Hive vs. Quasardb vs. Riak KV vs. Vertica

Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonHive  Xexclude from comparisonQuasardb  Xexclude from comparisonRiak KV  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLdata warehouse software for querying and managing large distributed datasets, built on HadoopDistributed, high-performance timeseries databaseDistributed, fault tolerant key-value storeCloud 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 DBMSRelational DBMSTime Series DBMSKey-value store infowith links between data sets and object tags for the creation of secondary indexesRelational DBMS infoColumn oriented
Secondary database modelsDocument storeSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score4.10
Rank#82  Overall
#9  Key-value stores
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitewww.citusdata.comhive.apache.orgquasar.aiwww.vertica.com
Technical documentationdocs.citusdata.comcwiki.apache.org/­confluence/­display/­Hive/­Homedoc.quasar.ai/­masterwww.tiot.jp/­riak-docs/­riak/­kv/­latestvertica.com/­documentation
DeveloperApache Software Foundation infoinitially developed by FacebookquasardbOpenSource, formerly Basho TechnologiesOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20102012200920092005
Current release8.1, December 20183.1.3, April 20223.14.1, January 20243.2.0, December 202212.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availableOpen Source infoApache Version 2commercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoApache version 2, commercial enterprise editioncommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonononono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCJavaC++ErlangC++
Server operating systemsLinuxAll OS with a Java VMBSD
Linux
OS X
Windows
Linux
OS X
Linux
Data schemeyesyesschema-freeschema-freeYes, 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 dateyesyesyes infointeger and binarynoyes
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.yes infospecific XML type available, but no XML query functionalitynonono
Secondary indexesyesyesyes infowith tagsrestrictedNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyes infostandard, with numerous extensionsSQL-like DML and DDL statementsSQL-like query languagenoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Thrift
HTTP APIHTTP API
Native Erlang Interface
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C++
Java
PHP
Python
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.yes infouser defined functions and integration of map-reducenoErlangyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesnonoyes infopre-commit hooks and post-commit hooksyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoconsistent hashingSharding infono "single point of failure"horizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsselectable replication factorSource-replica replication with selectable replication factorselectable 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 methodsnoyes infoquery execution via MapReducewith Hadoop integrationyesno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonono infolinks between data sets can be storedyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoby using LevelDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoTransient modeno
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and rolesCryptographically strong user authentication and audit trailyes, using Riak Securityfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
CitusHiveQuasardbRiak KVVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more
Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
» more

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More resources
CitusHiveQuasardbRiak KVVertica infoOpenText™ Vertica™
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