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DBMS > Databricks vs. Firebird vs. Hazelcast

System Properties Comparison Databricks vs. Firebird vs. Hazelcast

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonFirebird  Xexclude from comparisonHazelcast  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 widely adopted in-memory data grid
Primary database modelDocument store
Relational DBMS
Relational DBMSKey-value store
Secondary database modelsDocument store infoJSON support with IMDG 3.12
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
Score5.97
Rank#57  Overall
#6  Key-value stores
Websitewww.databricks.comwww.firebirdsql.orghazelcast.com
Technical documentationdocs.databricks.comwww.firebirdsql.org/­en/­reference-manualshazelcast.org/­imdg/­docs
DeveloperDatabricksFirebird FoundationHazelcast
Initial release20132000 infoAs fork of Borland's InterBase2008
Current release5.0.0, January 20245.3.6, November 2023
License infoCommercial or Open SourcecommercialOpen Source infoInitial Developer's Public LicenseOpen Source infoApache Version 2; commercial licenses available
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++Java
Server operating systemshostedAIX
FreeBSD
HP-UX
Linux
OS X
server-less infoFirebird Embedded Server
Solaris
Unix
Windows
All OS with a Java VM
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-free
Typing infopredefined data types such as float or dateyesyes
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.yesyes infothe object must implement a serialization strategy
Secondary indexesyesyesyes
SQL infoSupport of SQLwith Databricks SQLyesSQL-like query language
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
C/C++ API
JDBC infoJaybird
ODBC
OLE DB
JCache
JPA
Memcached protocol
RESTful HTTP API
Supported programming languagesPython
R
Scala
C
C#
C++
Delphi
Java
JavaScript infoNode.js
Lua
Perl
PHP
Python
Ruby
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesPSQLyes infoEvent Listeners, Executor Services
Triggersyesyes infoEvents
Partitioning methods infoMethods for storing different data on different nodesnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationyes infoReplicated Map
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus Algorithm
Foreign keys infoReferential integrityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDone or two-phase-commit; repeatable reads; read commited
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 controlUsers with fine-grained authorization conceptRole-based access control
More information provided by the system vendor
DatabricksFirebirdHazelcast
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksFirebirdHazelcast
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