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DBMS > Apache Phoenix vs. InfinityDB vs. JaguarDB vs. Vitess

System Properties Comparison Apache Phoenix vs. InfinityDB vs. JaguarDB vs. Vitess

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonInfinityDB  Xexclude from comparisonJaguarDB  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseA Java embedded Key-Value Store which extends the Java Map interfacePerformant, highly scalable DBMS for AI and IoT applicationsScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelRelational DBMSKey-value storeKey-value store
Vector DBMS
Relational 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
Score0.00
Rank#378  Overall
#57  Key-value stores
Score0.00
Rank#383  Overall
#60  Key-value stores
#13  Vector DBMS
Score0.82
Rank#209  Overall
#97  Relational DBMS
Websitephoenix.apache.orgboilerbay.comwww.jaguardb.comvitess.io
Technical documentationphoenix.apache.orgboilerbay.com/­infinitydb/­manualwww.jaguardb.com/­support.htmlvitess.io/­docs
DeveloperApache Software FoundationBoiler Bay Inc.DataJaguar, Inc.The Linux Foundation, PlanetScale
Initial release2014200220152013
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20194.03.3 July 202315.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoGPL V3.0Open Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC++ infothe server part. Clients available in other languagesGo
Server operating systemsLinux
Unix
Windows
All OS with a Java VMLinuxDocker
Linux
macOS
Data schemeyes infolate-bound, schema-on-read capabilitiesyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeyesyes
Typing infopredefined data types such as float or dateyesyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyesyes
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 indexesyesno infomanual creation possible, using inversions based on multi-value capabilityyesyes
SQL infoSupport of SQLyesnoA subset of ANSI SQL is implemented infobut no views, foreign keys, triggersyes infowith proprietary extensions
APIs and other access methodsJDBCAccess via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
JDBC
ODBC
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
JavaC
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functionsnonoyes infoproprietary syntax
Triggersnononoyes
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 replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate Consistency infoREAD-COMMITTED or SERIALIZEDEventual ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynono infomanual creation possible, using inversions based on multi-value capabilitynoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoOptimistic locking for transactions; no isolation for bulk loadsnoACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engine
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-tenancynorights management via user accountsUsers with fine-grained authorization concept infono user groups or roles

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More resources
Apache PhoenixInfinityDBJaguarDBVitess
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Recent citations in the news

Supercharge SQL on Your Data in Apache HBase with Apache Phoenix | Amazon Web Services
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4 February 2016, InfoWorld

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13 November 2019, TechTarget

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19 February 2019, InfoQ.com

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