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DBMS > Apache Phoenix vs. Firebird vs. HEAVY.AI

System Properties Comparison Apache Phoenix vs. Firebird vs. HEAVY.AI

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonFirebird  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseFirebird is an open source RDBMS forked from Borland's InterBaseA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware
Primary database modelRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.84
Rank#122  Overall
#59  Relational DBMS
Score17.28
Rank#32  Overall
#20  Relational DBMS
Score1.25
Rank#161  Overall
#72  Relational DBMS
Websitephoenix.apache.orgwww.firebirdsql.orggithub.com/­heavyai/­heavydb
www.heavy.ai
Technical documentationphoenix.apache.orgwww.firebirdsql.org/­en/­reference-manualsdocs.heavy.ai
DeveloperApache Software FoundationFirebird FoundationHEAVY.AI, Inc.
Initial release20142000 infoAs fork of Borland's InterBase2016
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20195.0.1, August 20245.10, January 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoInitial Developer's Public LicenseOpen Source infoApache Version 2; enterprise edition available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++C++ and CUDA
Server operating systemsLinux
Unix
Windows
AIX
FreeBSD
HP-UX
Linux
OS X
server-less infoFirebird Embedded Server
Solaris
Unix
Windows
Linux
Data schemeyes infolate-bound, schema-on-read capabilitiesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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
SQL infoSupport of SQLyesyesyes
APIs and other access methodsJDBCADO.NET
C/C++ API
JDBC infoJaybird
ODBC
OLE DB
JDBC
ODBC
Thrift
Vega
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C
C#
C++
Delphi
Java
JavaScript infoNode.js
Lua
Perl
PHP
Python
Ruby
All languages supporting JDBC/ODBC/Thrift
Python
Server-side scripts infoStored proceduresuser defined functionsPSQLno
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infoRound robin
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replicationMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes infoFeatures a multi-generational MVCC architecture, readers do not block writersyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyUsers with fine-grained authorization conceptfine grained access rights according to SQL-standard

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More resources
Apache PhoenixFirebirdHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022
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