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DBMS > Databricks vs. Firebird vs. Google Cloud Datastore vs. jBASE

System Properties Comparison Databricks vs. Firebird vs. Google Cloud Datastore vs. jBASE

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonFirebird  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonjBASE  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 InterBaseAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA robust multi-value DBMS comprising development tools and middleware
Primary database modelDocument store
Relational DBMS
Relational DBMSDocument storeMultivalue DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score20.50
Rank#30  Overall
#18  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score1.49
Rank#156  Overall
#3  Multivalue DBMS
Websitewww.databricks.comwww.firebirdsql.orgcloud.google.com/­datastorewww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-jbase
Technical documentationdocs.databricks.comwww.firebirdsql.org/­en/­reference-manualscloud.google.com/­datastore/­docsdocs.rocketsoftware.com/­bundle?labelkey=jbase_5.9
DeveloperDatabricksFirebird FoundationGoogleRocket Software (formerly Zumasys)
Initial release20132000 infoAs fork of Borland's InterBase20081991
Current release5.0.0, January 20245.7
License infoCommercial or Open SourcecommercialOpen Source infoInitial Developer's Public Licensecommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++
Server operating systemshostedAIX
FreeBSD
HP-UX
Linux
OS X
server-less infoFirebird Embedded Server
Solaris
Unix
Windows
hostedAIX
Linux
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyes, details hereoptional
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.yesnoyes
Secondary indexesyesyesyes
SQL infoSupport of SQLwith Databricks SQLyesSQL-like query language (GQL)Embedded SQL for jBASE in BASIC
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
C/C++ API
JDBC infoJaybird
ODBC
OLE DB
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API
Supported programming languagesPython
R
Scala
C
C#
C++
Delphi
Java
JavaScript infoNode.js
Lua
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Basic
Jabbascript
Java
Server-side scripts infoStored proceduresuser defined functions and aggregatesPSQLusing Google App Engineyes
TriggersyesCallbacks using the Google Apps Engineyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationMulti-source replication using Paxosyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoFeatures a multi-generational MVCC architecture, readers do not block writersyesyes
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.nonoyes
User concepts infoAccess controlUsers with fine-grained authorization conceptAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights can be defined down to the item level
More information provided by the system vendor
DatabricksFirebirdGoogle Cloud DatastorejBASE
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksFirebirdGoogle Cloud DatastorejBASE
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