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DBMS > Databricks vs. Firebird vs. Tkrzw

System Properties Comparison Databricks vs. Firebird vs. Tkrzw

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonFirebird  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Firebird is an open source RDBMS forked from Borland's InterBaseA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelDocument store
Relational DBMS
Relational DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score20.82
Rank#30  Overall
#18  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitewww.databricks.comwww.firebirdsql.orgdbmx.net/­tkrzw
Technical documentationdocs.databricks.comwww.firebirdsql.org/­en/­reference-manuals
DeveloperDatabricksFirebird FoundationMikio Hirabayashi
Initial release20132000 infoAs fork of Borland's InterBase2020
Current release5.0.0, January 20240.9.3, August 2020
License infoCommercial or Open SourcecommercialOpen Source infoInitial Developer's Public LicenseOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC and C++C++
Server operating systemshostedAIX
FreeBSD
HP-UX
Linux
OS X
server-less infoFirebird Embedded Server
Solaris
Unix
Windows
Linux
macOS
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-free
Typing infopredefined data types such as float or dateyesno
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.yesno
Secondary indexesyesyes
SQL infoSupport of SQLwith Databricks SQLyesno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
C/C++ API
JDBC infoJaybird
ODBC
OLE DB
Supported programming languagesPython
R
Scala
C
C#
C++
Delphi
Java
JavaScript infoNode.js
Lua
Perl
PHP
Python
Ruby
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesPSQLno
Triggersyesno
Partitioning methods infoMethods for storing different data on different nodesnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID
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 infousing specific database classes
User concepts infoAccess controlUsers with fine-grained authorization conceptno
More information provided by the system vendor
DatabricksFirebirdTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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