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DBMS > Apache Phoenix vs. FeatureBase vs. Spark SQL vs. VictoriaMetrics

System Properties Comparison Apache Phoenix vs. FeatureBase vs. Spark SQL vs. VictoriaMetrics

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonFeatureBase  Xexclude from comparisonSpark SQL  Xexclude from comparisonVictoriaMetrics  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseReal-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.Spark SQL is a component on top of 'Spark Core' for structured data processingA fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelRelational DBMSRelational DBMSRelational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score0.31
Rank#292  Overall
#135  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score1.23
Rank#172  Overall
#15  Time Series DBMS
Websitephoenix.apache.orgwww.featurebase.comspark.apache.org/­sqlvictoriametrics.com
Technical documentationphoenix.apache.orgdocs.featurebase.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperApache Software FoundationMolecula and Pilosa Open Source ContributorsApache Software FoundationVictoriaMetrics
Initial release2014201720142018
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20192022, May 20223.5.0 ( 2.13), September 2023v1.91, May 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaGoScalaGo
Server operating systemsLinux
Unix
Windows
Linux
macOS
Linux
OS X
Windows
FreeBSD
Linux
macOS
OpenBSD
Data schemeyes infolate-bound, schema-on-read capabilitiesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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
SQL infoSupport of SQLyesSQL queriesSQL-like DML and DDL statementsno
APIs and other access methodsJDBCgRPC
JDBC
Kafka Connector
ODBC
JDBC
ODBC
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Java
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsnono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesnoneSynchronous replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes, using Linux fsyncyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnono
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyno

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More resources
Apache PhoenixFeatureBaseSpark SQLVictoriaMetrics
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