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DBMS > Databricks vs. EDB Postgres vs. Google BigQuery

System Properties Comparison Databricks vs. EDB Postgres vs. Google BigQuery

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonEDB Postgres  Xexclude from comparisonGoogle BigQuery  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.The EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.Large scale data warehouse service with append-only tables
Primary database modelDocument store
Relational DBMS
Relational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score60.82
Rank#19  Overall
#3  Document stores
#13  Relational DBMS
Score2.76
Rank#115  Overall
#58  Relational DBMS
Score54.43
Rank#21  Overall
#14  Relational DBMS
Websitedatabricks.comwww.enterprisedb.comcloud.google.com/­bigquery
Technical documentationdatabricks.com/­documentationwww.enterprisedb.com/­edb-docscloud.google.com/­bigquery/­docs
DeveloperDatabricksEnterpriseDBGoogle
Initial release201320052010
Current release14, December 2021
License infoCommercial or Open SourceOpen Sourcecommercial infoBSD for PostgreSQL-componentscommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC
Server operating systemshostedLinux
Windows
hosted
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or dateyesyes
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.yesyes infospecific XML-type available, but no XML query functionality.no
Secondary indexesyesyesno
SQL infoSupport of SQLwith Databricks SQLyes infostandard with numerous extensionsyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
RESTful HTTP/JSON API
Supported programming languagesPython
R
Scala
.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl
.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.user defined functions infoin JavaScript
Triggersyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning infoby hash, list or rangenone
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
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 integrityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno infoSince BigQuery is designed for querying data
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)

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More resources
DatabricksEDB PostgresGoogle BigQuery
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