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DBMS > Citus vs. HBase vs. KeyDB vs. RDF4J vs. Vertica

System Properties Comparison Citus vs. HBase vs. KeyDB vs. RDF4J vs. Vertica

Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonHBase  Xexclude from comparisonKeyDB  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLWide-column store based on Apache Hadoop and on concepts of BigTableAn ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocolsRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.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 DBMSWide column storeKey-value storeRDF storeRelational 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
Score30.50
Rank#26  Overall
#2  Wide column stores
Score0.71
Rank#226  Overall
#33  Key-value stores
Score0.69
Rank#230  Overall
#9  RDF stores
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitewww.citusdata.comhbase.apache.orggithub.com/­Snapchat/­KeyDB
keydb.dev
rdf4j.orgwww.vertica.com
Technical documentationdocs.citusdata.comhbase.apache.org/­book.htmldocs.keydb.devrdf4j.org/­documentationvertica.com/­documentation
DeveloperApache Software Foundation infoApache top-level project, originally developed by PowersetEQ Alpha Technology Ltd.Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.OpenText infopreviously Micro Focus and Hewlett Packard
Initial release20102008201920042005
Current release8.1, December 20182.3.4, January 202112.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availableOpen Source infoApache version 2Open Source infoBSD-3Open Source infoEclipse Distribution License (EDL), v1.0.commercial 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

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Implementation languageCJavaC++JavaC++
Server operating systemsLinuxLinux
Unix
Windows infousing Cygwin
LinuxLinux
OS X
Unix
Windows
Linux
Data schemeyesschema-free, schema definition possibleschema-freeyes infoRDF SchemasYes, 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 dateyesoptions to bring your own types, AVROpartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexesyesyes
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 indexesyesnoyes infoby using the Redis Search moduleyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyes infostandard, with numerous extensionsnononoFull 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
Java API
RESTful HTTP API
Thrift
Proprietary protocol infoRESP - REdis Serialization ProtocoJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
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
C#
C++
Groovy
Java
PHP
Python
Scala
C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic
Java
PHP
Python
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 infoCoprocessors in JavaLuayesyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesyesnoyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnonehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
noneMulti-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 methodsnoyesnonono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyEventual Consistency
Strong eventual consistency with CRDTs
Immediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDSingle row ACID (across millions of columns)Optimistic locking, atomic execution of commands blocks and scriptsACID infoIsolation support depends on the API usedACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logsyes infoin-memory storage is supported as wellyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACsimple password-based access control and ACLnofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
CitusHBaseKeyDBRDF4J infoformerly known as SesameVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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More resources
CitusHBaseKeyDBRDF4J infoformerly known as SesameVertica infoOpenText™ Vertica™
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