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

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

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonFirebird  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopFirebird 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 modelsDocument storeSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score20.82
Rank#30  Overall
#18  Relational DBMS
Score1.77
Rank#141  Overall
#65  Relational DBMS
Websiteimpala.apache.orgwww.firebirdsql.orggithub.com/­heavyai/­heavydb
www.heavy.ai
Technical documentationimpala.apache.org/­impala-docs.htmlwww.firebirdsql.org/­en/­reference-manualsdocs.heavy.ai
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaFirebird FoundationHEAVY.AI, Inc.
Initial release20132000 infoAs fork of Borland's InterBase2016
Current release4.1.0, June 20225.0.0, January 20245.10, January 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2Open 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 languageC++C and C++C++ and CUDA
Server operating systemsLinuxAIX
FreeBSD
HP-UX
Linux
OS X
server-less infoFirebird Embedded Server
Solaris
Unix
Windows
Linux
Data schemeyesyesyes
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 SQLSQL-like DML and DDL statementsyesyes
APIs and other access methodsJDBC
ODBC
ADO.NET
C/C++ API
JDBC infoJaybird
ODBC
OLE DB
JDBC
ODBC
Thrift
Vega
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Delphi
Java
JavaScript infoNode.js
Lua
Perl
PHP
Python
Ruby
All languages supporting JDBC/ODBC/Thrift
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducePSQLno
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infoRound robin
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDno
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.noyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosUsers with fine-grained authorization conceptfine grained access rights according to SQL-standard

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