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DBMS > Apache Phoenix vs. Hawkular Metrics vs. RDFox vs. Vertica

System Properties Comparison Apache Phoenix vs. Hawkular Metrics vs. RDFox vs. Vertica

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonRDFox  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.High performance knowledge graph and semantic reasoning engineCloud 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 DBMSGraph DBMS
RDF store
Relational DBMS infoColumn oriented
Secondary database modelsRelational DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score0.23
Rank#308  Overall
#25  Graph DBMS
#14  RDF stores
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitephoenix.apache.orgwww.hawkular.orgwww.oxfordsemantic.techwww.vertica.com
Technical documentationphoenix.apache.orgwww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.oxfordsemantic.techvertica.com/­documentation
DeveloperApache Software FoundationCommunity supported by Red HatOxford Semantic TechnologiesOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2014201420172005
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20196.0, Septermber 202212.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0commercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenononono 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 languageJavaJavaC++C++
Server operating systemsLinux
Unix
Windows
Linux
OS X
Windows
Linux
macOS
Windows
Linux
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-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 dateyesyesyesyes
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 indexesyesnoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyesnonoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBCHTTP RESTRESTful HTTP API
SPARQL 1.1
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Go
Java
Python
Ruby
C
Java
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresuser defined functionsnoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyes infovia Hawkular Alertingyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on Cassandrahorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
selectable replication factor infobased on Cassandrareplication via a shared file systemMulti-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 methodsHadoop integrationnono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setupsImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancynoRoles, resources, and access typesfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Apache PhoenixHawkular MetricsRDFoxVertica 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...
» 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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Apache PhoenixHawkular MetricsRDFoxVertica infoOpenText™ Vertica™
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