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

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

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonDrizzle  Xexclude from comparisonInfinityDB  Xexclude from comparisonMonetDB  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.A Java embedded Key-Value Store which extends the Java Map interfaceA relational database management system that stores data in columns
Primary database modelRelational DBMSRelational DBMSKey-value storeRelational 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
Score1.72
Rank#145  Overall
#67  Relational DBMS
Websitephoenix.apache.orgboilerbay.comwww.monetdb.org
Technical documentationphoenix.apache.orgboilerbay.com/­infinitydb/­manualwww.monetdb.org/­Documentation
DeveloperApache Software FoundationDrizzle project, originally started by Brian AkerBoiler Bay Inc.MonetDB BV
Initial release2014200820022004
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20197.2.4, September 20124.0Dec2023 (11.49), December 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoGNU GPLcommercialOpen 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 languageJavaC++JavaC
Server operating systemsLinux
Unix
Windows
FreeBSD
Linux
OS X
All OS with a Java VMFreeBSD
Linux
OS X
Solaris
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesyesyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeyes
Typing infopredefined data types such as float or dateyesyesyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyes
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.nono
Secondary indexesyesyesno infomanual creation possible, using inversions based on multi-value capabilityyes
SQL infoSupport of SQLyesyes infowith proprietary extensionsnoyes infoSQL 2003 with some extensions
APIs and other access methodsJDBCJDBCAccess via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
JDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C
C++
Java
PHP
JavaC
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Server-side scripts infoStored proceduresuser defined functionsnonoyes, in SQL, C, R
Triggersnono infohooks for callbacks inside the server can be used.noyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding via remote tables
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
nonenone infoSource-replica replication available in experimental status
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 SERIALIZED
Foreign keys infoReferential integritynoyesno infomanual creation possible, using inversions based on multi-value capabilityyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoOptimistic locking for transactions; no isolation for bulk loadsACID
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.yesno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyPluggable authentication mechanisms infoe.g. LDAP, HTTPnofine grained access rights according to SQL-standard

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Apache PhoenixDrizzleInfinityDBMonetDB
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