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DBMS > Databricks vs. Graph Engine vs. Microsoft Azure Table Storage vs. PostgreSQL

System Properties Comparison Databricks vs. Graph Engine vs. Microsoft Azure Table Storage vs. PostgreSQL

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonMicrosoft Azure Table Storage  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.A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineA Wide Column Store for rapid development using massive semi-structured datasetsWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL
Primary database modelDocument store
Relational DBMS
Graph DBMS
Key-value store
Wide column storeRelational 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
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
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.67
Rank#232  Overall
#21  Graph DBMS
#34  Key-value stores
Score4.04
Rank#77  Overall
#6  Wide column stores
Score636.25
Rank#4  Overall
#4  Relational DBMS
Websitewww.databricks.comwww.graphengine.ioazure.microsoft.com/­en-us/­services/­storage/­tableswww.postgresql.org
Technical documentationdocs.databricks.comwww.graphengine.io/­docs/­manualwww.postgresql.org/­docs
DeveloperDatabricksMicrosoftMicrosoftPostgreSQL Global Development Group infowww.postgresql.org/­developer
Initial release2013201020121989 info1989: Postgres, 1996: PostgreSQL
Current release16.3, May 2024
License infoCommercial or Open SourcecommercialOpen Source infoMIT LicensecommercialOpen Source infoBSD
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation language.NET and CC
Server operating systemshosted.NEThostedFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes
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.yesnonoyes infospecific XML-type available, but no XML query functionality.
Secondary indexesyesnoyes
SQL infoSupport of SQLwith Databricks SQLnonoyes infostandard with numerous extensions
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
RESTful HTTP APIRESTful HTTP APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesPython
R
Scala
C#
C++
F#
Visual Basic
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesnouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningSharding infoImplicit feature of the cloud servicepartitioning by range, list and (since PostgreSQL 11) by hash
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes 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 methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnooptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnono
User concepts infoAccess controlAccess rights based on private key authentication or shared access signaturesfine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksGraph Engine infoformer name: TrinityMicrosoft Azure Table StoragePostgreSQL
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksGraph Engine infoformer name: TrinityMicrosoft Azure Table StoragePostgreSQL
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