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DBMS > Databricks vs. EsgynDB vs. Microsoft Azure AI Search vs. PlanetScale vs. PostgreSQL

System Properties Comparison Databricks vs. EsgynDB vs. Microsoft Azure AI Search vs. PlanetScale vs. PostgreSQL

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonEsgynDB  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonPlanetScale  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.Enterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionSearch-as-a-service for web and mobile app developmentScalable, distributed, serverless MySQL database platform built on top of VitessWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL
Primary database modelDocument store
Relational DBMS
Relational DBMSSearch engineRelational DBMSRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.
Secondary database modelsVector DBMSDocument store
Spatial DBMS
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
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score5.59
Rank#63  Overall
#7  Search engines
Score1.59
Rank#151  Overall
#70  Relational DBMS
Score645.54
Rank#4  Overall
#4  Relational DBMS
Websitewww.databricks.comwww.esgyn.cnazure.microsoft.com/­en-us/­services/­searchplanetscale.comwww.postgresql.org
Technical documentationdocs.databricks.comlearn.microsoft.com/­en-us/­azure/­searchplanetscale.com/­docswww.postgresql.org/­docs
DeveloperDatabricksEsgynMicrosoftPlanetScalePostgreSQL Global Development Group infowww.postgresql.org/­developer
Initial release20132015201520201989 info1989: Postgres, 1996: PostgreSQL
Current releaseV116.3, May 2024
License infoCommercial or Open SourcecommercialcommercialcommercialcommercialOpen Source infoBSD
Cloud-based only infoOnly available as a cloud serviceyesnoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaGoC
Server operating systemshostedLinuxhostedDocker
Linux
macOS
FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 indexesyesyesyesyesyes
SQL infoSupport of SQLwith Databricks SQLyesnoyes infowith proprietary extensionsyes infostandard with numerous extensions
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
RESTful HTTP APIADO.NET
JDBC
MySQL protocol
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesPython
R
Scala
All languages supporting JDBC/ODBC/ADO.NetC#
Java
JavaScript
Python
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresuser defined functions and aggregatesJava Stored Proceduresnoyes infoproprietary syntaxuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.
Triggersnonoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceShardingpartitioning by range, list and (since PostgreSQL 11) by hash
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication between multi datacentersyes infoImplicit feature of the cloud serviceMulti-source replication
Source-replica replication
Source-replica replication infoother methods possible by using 3rd party extensions
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Immediate Consistency
Foreign keys infoReferential integrityyesnoyes infonot for MyISAM storage engineyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID at shard levelACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engineyes
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.nononoyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardyes infousing Azure authenticationUsers with fine-grained authorization concept infono user groups or rolesfine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksEsgynDBMicrosoft Azure AI SearchPlanetScalePostgreSQL
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksEsgynDBMicrosoft Azure AI SearchPlanetScalePostgreSQL
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