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DBMS > Apache Phoenix vs. InfinityDB vs. PlanetScale vs. Solr

System Properties Comparison Apache Phoenix vs. InfinityDB vs. PlanetScale vs. Solr

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonInfinityDB  Xexclude from comparisonPlanetScale  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseA Java embedded Key-Value Store which extends the Java Map interfaceScalable, distributed, serverless MySQL database platform built on top of VitessA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSKey-value storeRelational DBMSSearch engine
Secondary database modelsDocument store
Spatial DBMS
Spatial 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#378  Overall
#57  Key-value stores
Score1.59
Rank#151  Overall
#70  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Websitephoenix.apache.orgboilerbay.complanetscale.comsolr.apache.org
Technical documentationphoenix.apache.orgboilerbay.com/­infinitydb/­manualplanetscale.com/­docssolr.apache.org/­resources.html
DeveloperApache Software FoundationBoiler Bay Inc.PlanetScaleApache Software Foundation
Initial release2014200220202006
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20194.09.6.0, April 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaGoJava
Server operating systemsLinux
Unix
Windows
All OS with a Java VMDocker
Linux
macOS
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyes infolate-bound, schema-on-read capabilitiesyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyesyes infosupports customizable data types and automatic typing
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.nonoyes
Secondary indexesyesno infomanual creation possible, using inversions based on multi-value capabilityyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLyesnoyes infowith proprietary extensionsSolr Parallel SQL Interface
APIs and other access methodsJDBCAccess via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
ADO.NET
JDBC
MySQL protocol
ODBC
Java API
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
JavaAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresuser defined functionsnoyes infoproprietary syntaxJava plugins
Triggersnonoyesyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
noneMulti-source replication
Source-replica replication
yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate Consistency infoREAD-COMMITTED or SERIALIZEDEventual Consistency across shards
Immediate Consistency within a shard
Eventual Consistency
Foreign keys infoReferential integritynono infomanual creation possible, using inversions based on multi-value capabilityyes infonot for MyISAM storage engineno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoOptimistic locking for transactions; no isolation for bulk loadsACID at shard leveloptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyes infotable locks or row locks depending on storage engineyes
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.yesnoyesyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancynoUsers with fine-grained authorization concept infono user groups or rolesyes

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Apache PhoenixInfinityDBPlanetScaleSolr
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