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DBMS > Databricks vs. Firebird vs. Heroic vs. Microsoft Azure Data Explorer vs. PostgreSQL

System Properties Comparison Databricks vs. Firebird vs. Heroic vs. Microsoft Azure Data Explorer vs. PostgreSQL

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonFirebird  Xexclude from comparisonHeroic  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonPostgreSQL  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 InterBaseTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchFully managed big data interactive analytics platformWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL
Primary database modelDocument store
Relational DBMS
Relational DBMSTime Series DBMSRelational DBMS infocolumn orientedRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.
Secondary database modelsDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
Document store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
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
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score645.54
Rank#4  Overall
#4  Relational DBMS
Websitewww.databricks.comwww.firebirdsql.orggithub.com/­spotify/­heroicazure.microsoft.com/­services/­data-explorerwww.postgresql.org
Technical documentationdocs.databricks.comwww.firebirdsql.org/­en/­reference-manualsspotify.github.io/­heroicdocs.microsoft.com/­en-us/­azure/­data-explorerwww.postgresql.org/­docs
DeveloperDatabricksFirebird FoundationSpotifyMicrosoftPostgreSQL Global Development Group infowww.postgresql.org/­developer
Initial release20132000 infoAs fork of Borland's InterBase201420191989 info1989: Postgres, 1996: PostgreSQL
Current release5.0.0, January 2024cloud service with continuous releases16.3, May 2024
License infoCommercial or Open SourcecommercialOpen Source infoInitial Developer's Public LicenseOpen Source infoApache 2.0commercialOpen Source infoBSD
Cloud-based only infoOnly available as a cloud serviceyesnonoyesno
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Implementation languageC and C++JavaC
Server operating systemshostedAIX
FreeBSD
HP-UX
Linux
OS X
server-less infoFirebird Embedded Server
Solaris
Unix
Windows
hostedFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes
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.yesnoyesyes infospecific XML-type available, but no XML query functionality.
Secondary indexesyesyesyes infovia Elasticsearchall fields are automatically indexedyes
SQL infoSupport of SQLwith Databricks SQLyesnoKusto Query Language (KQL), SQL subsetyes infostandard with numerous extensions
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
C/C++ API
JDBC infoJaybird
ODBC
OLE DB
HQL (Heroic Query Language, a JSON-based language)
HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesPython
R
Scala
C
C#
C++
Delphi
Java
JavaScript infoNode.js
Lua
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresuser defined functions and aggregatesPSQLnoYes, possible languages: KQL, Python, Ruser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.
Triggersyesnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoImplicit feature of the cloud servicepartitioning by range, list and (since PostgreSQL 11) by hash
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication infoother methods possible by using 3rd party extensions
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnonoACID
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.nononono
User concepts infoAccess controlUsers with fine-grained authorization conceptAzure Active Directory Authenticationfine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksFirebirdHeroicMicrosoft Azure Data ExplorerPostgreSQL
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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