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DBMS > Apache Phoenix vs. InfinityDB vs. Kdb vs. MonetDB

System Properties Comparison Apache Phoenix vs. InfinityDB vs. Kdb vs. MonetDB

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonInfinityDB  Xexclude from comparisonKdb  Xexclude from comparisonMonetDB  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseA Java embedded Key-Value Store which extends the Java Map interfaceHigh performance Time Series DBMSA relational database management system that stores data in columns
Primary database modelRelational DBMSKey-value storeTime Series DBMS
Vector DBMS
Relational DBMS
Secondary database modelsRelational DBMSDocument 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
Score7.55
Rank#53  Overall
#3  Time Series DBMS
#1  Vector DBMS
Score1.72
Rank#145  Overall
#67  Relational DBMS
Websitephoenix.apache.orgboilerbay.comkx.comwww.monetdb.org
Technical documentationphoenix.apache.orgboilerbay.com/­infinitydb/­manualcode.kx.comwww.monetdb.org/­Documentation
DeveloperApache Software FoundationBoiler Bay Inc.Kx Systems, a division of First Derivatives plcMonetDB BV
Initial release201420022000 infokdb was released 2000, kdb+ in 20032004
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20194.03.6, May 2018Dec2023 (11.49), December 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial infofree 32-bit versionOpen Source infoMozilla Public License 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaqC
Server operating systemsLinux
Unix
Windows
All OS with a Java VMLinux
OS X
Solaris
Windows
FreeBSD
Linux
OS X
Solaris
Windows
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.nonoyes
Secondary indexesyesno infomanual creation possible, using inversions based on multi-value capabilityyes infotable attribute 'grouped'yes
SQL infoSupport of SQLyesnoSQL-like query language (q)yes infoSQL 2003 with some extensions
APIs and other access methodsJDBCAccess via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
JDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
JavaC
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Server-side scripts infoStored proceduresuser defined functionsnouser defined functionsyes, in SQL, C, R
Triggersnonoyes infowith viewsyes
Partitioning methods infoMethods for storing different data on different nodesShardingnonehorizontal partitioningSharding via remote tables
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
noneSource-replica replicationnone infoSource-replica replication available in experimental status
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnono infosimilar paradigm used for internal processingno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate Consistency infoREAD-COMMITTED or SERIALIZEDImmediate Consistency
Foreign keys infoReferential integritynono infomanual creation possible, using inversions based on multi-value capabilityyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoOptimistic locking for transactions; no isolation for bulk loadsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.yesnoyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancynorights management via user accountsfine grained access rights according to SQL-standard
More information provided by the system vendor
Apache PhoenixInfinityDBKdbMonetDB
Specific characteristicsIntegrated columnar database & programming system for streaming, real time and historical...
» more
Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more
Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsupon request
» more

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Apache PhoenixInfinityDBKdbMonetDB
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