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DBMS > Apache Phoenix vs. Derby vs. Hawkular Metrics vs. PlanetScale vs. Splice Machine

System Properties Comparison Apache Phoenix vs. Derby vs. Hawkular Metrics vs. PlanetScale vs. Splice Machine

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonDerby infooften called Apache Derby, originally IBM Cloudscape; contained in the Java SDK as JavaDB  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonPlanetScale  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseFull-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Scalable, distributed, serverless MySQL database platform built on top of VitessOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSRelational DBMSTime Series DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score4.71
Rank#69  Overall
#37  Relational DBMS
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score1.59
Rank#151  Overall
#70  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitephoenix.apache.orgdb.apache.org/­derbywww.hawkular.orgplanetscale.comsplicemachine.com
Technical documentationphoenix.apache.orgdb.apache.org/­derby/­manuals/­index.htmlwww.hawkular.org/­hawkular-metrics/­docs/­user-guideplanetscale.com/­docssplicemachine.com/­how-it-works
DeveloperApache Software FoundationApache Software FoundationCommunity supported by Red HatPlanetScaleSplice Machine
Initial release20141997201420202014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 201910.17.1.0, November 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache version 2Open Source infoApache 2.0commercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJavaGoJava
Server operating systemsLinux
Unix
Windows
All OS with a Java VMLinux
OS X
Windows
Docker
Linux
macOS
Linux
OS X
Solaris
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.noyesno
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLyesyesnoyes infowith proprietary extensionsyes
APIs and other access methodsJDBCJDBCHTTP RESTADO.NET
JDBC
MySQL protocol
ODBC
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
JavaGo
Java
Python
Ruby
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsJava Stored Proceduresnoyes infoproprietary syntaxyes infoJava
Triggersnoyesyes infovia Hawkular Alertingyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infobased on CassandraShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replicationselectable replication factor infobased on CassandraMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual Consistency across shards
Immediate Consistency within a shard
Immediate Consistency
Foreign keys infoReferential integritynoyesnoyes infonot for MyISAM storage engineyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID at shard levelACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engineyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyesyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyfine grained access rights according to SQL-standardnoUsers with fine-grained authorization concept infono user groups or rolesAccess rights for users, groups and roles according to SQL-standard

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More resources
Apache PhoenixDerby infooften called Apache Derby, originally IBM Cloudscape; contained in the Java SDK as JavaDBHawkular MetricsPlanetScaleSplice Machine
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