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

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

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparisonYottaDB  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.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.A fast and solid embedded Key-value store
Primary database modelRelational DBMSTime Series DBMSRelational DBMS infoColumn orientedKey-value store
Secondary database modelsSpatial DBMS
Time Series DBMS
Relational DBMS infousing the Octo plugin
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
Score10.68
Rank#43  Overall
#27  Relational DBMS
Score0.20
Rank#317  Overall
#47  Key-value stores
Websitephoenix.apache.orgwww.hawkular.orgwww.vertica.comyottadb.com
Technical documentationphoenix.apache.orgwww.hawkular.org/­hawkular-metrics/­docs/­user-guidevertica.com/­documentationyottadb.com/­resources/­documentation
DeveloperApache Software FoundationCommunity supported by Red HatOpenText infopreviously Micro Focus and Hewlett PackardYottaDB, LLC
Initial release2014201420052001
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 201912.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0commercial infoLimited community edition freeOpen Source infoAGPL 3.0
Cloud-based only infoOnly available as a cloud servicenonono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containersno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC++C
Server operating systemsLinux
Unix
Windows
Linux
OS X
Windows
LinuxDocker
Linux
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.schema-free
Typing infopredefined data types such as float or dateyesyesyesno
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.nononono
Secondary indexesyesnoNo Indexes Required. Different internal optimization strategy, but same functionality included.no
SQL infoSupport of SQLyesnoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.by using the Octo plugin
APIs and other access methodsJDBCHTTP RESTADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
PostgreSQL wire protocol infousing the Octo plugin
Proprietary protocol
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Go
Java
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust
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 CassandraMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnono infoBi-directional Spark integrationno
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
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDoptimistic locking
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.yesnonoyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancynofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hashUsers and groups based on OS-security mechanisms
More information provided by the system vendor
Apache PhoenixHawkular MetricsVertica infoOpenText™ Vertica™YottaDB
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
Apache PhoenixHawkular MetricsVertica infoOpenText™ Vertica™YottaDB
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