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DBMS > Databricks vs. Firebird vs. jBASE vs. Microsoft Azure Synapse Analytics vs. WakandaDB

System Properties Comparison Databricks vs. Firebird vs. jBASE vs. Microsoft Azure Synapse Analytics vs. WakandaDB

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonFirebird  Xexclude from comparisonjBASE  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonWakandaDB  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 robust multi-value DBMS comprising development tools and middlewareElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelDocument store
Relational DBMS
Relational DBMSMultivalue DBMSRelational DBMSObject oriented 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
Score1.49
Rank#156  Overall
#3  Multivalue DBMS
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score0.10
Rank#356  Overall
#16  Object oriented DBMS
Websitewww.databricks.comwww.firebirdsql.orgwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-jbaseazure.microsoft.com/­services/­synapse-analyticswakanda.github.io
Technical documentationdocs.databricks.comwww.firebirdsql.org/­en/­reference-manualsdocs.rocketsoftware.com/­bundle?labelkey=jbase_5.9docs.microsoft.com/­azure/­synapse-analyticswakanda.github.io/­doc
DeveloperDatabricksFirebird FoundationRocket Software (formerly Zumasys)MicrosoftWakanda SAS
Initial release20132000 infoAs fork of Borland's InterBase199120162012
Current release5.0.0, January 20245.72.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourcecommercialOpen Source infoInitial Developer's Public LicensecommercialcommercialOpen Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC and C++C++C++, JavaScript
Server operating systemshostedAIX
FreeBSD
HP-UX
Linux
OS X
server-less infoFirebird Embedded Server
Solaris
Unix
Windows
AIX
Linux
Windows
hostedLinux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeyesyes
Typing infopredefined data types such as float or dateyesoptionalyesyes
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.yesyesnono
Secondary indexesyesyesyes
SQL infoSupport of SQLwith Databricks SQLyesEmbedded SQL for jBASE in BASICyesno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
C/C++ API
JDBC infoJaybird
ODBC
OLE DB
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API
ADO.NET
JDBC
ODBC
RESTful HTTP API
Supported programming languagesPython
R
Scala
C
C#
C++
Delphi
Java
JavaScript infoNode.js
Lua
Perl
PHP
Python
Ruby
.Net
Basic
Jabbascript
Java
C#
Java
PHP
JavaScript
Server-side scripts infoStored proceduresuser defined functions and aggregatesPSQLyesTransact SQLyes
Triggersyesyesnoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding, horizontal partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationyesyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraints
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoFeatures a multi-generational MVCC architecture, readers do not block writersyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlUsers with fine-grained authorization conceptAccess rights can be defined down to the item levelyesyes
More information provided by the system vendor
DatabricksFirebirdjBASEMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseWakandaDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksFirebirdjBASEMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseWakandaDB
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