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DBMS > Databricks vs. Fujitsu Enterprise Postgres vs. Google BigQuery

System Properties Comparison Databricks vs. Fujitsu Enterprise Postgres vs. Google BigQuery

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonFujitsu Enterprise 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.Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.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
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.31
Rank#285  Overall
#129  Relational DBMS
Score60.38
Rank#19  Overall
#13  Relational DBMS
Websitewww.databricks.comwww.postgresql.fastware.comcloud.google.com/­bigquery
Technical documentationdocs.databricks.comwww.postgresql.fastware.com/­product-manualscloud.google.com/­bigquery/­docs
DeveloperDatabricksPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyGoogle
Initial release20132010
Current releaseFujitsu Enterprise Postgres 14, January 2022
License infoCommercial or Open Sourcecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
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.yesno
Secondary indexesyesyesno
SQL infoSupport of SQLwith Databricks SQLyesyes
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
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesuser defined functionsuser defined functions infoin JavaScript
Triggersyesno
Partitioning methods infoMethods for storing different data on different nodespartitioning by range, list and by hashnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica 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.nono
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)
More information provided by the system vendor
DatabricksFujitsu Enterprise PostgresGoogle BigQuery
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
100% compatible with community PostgreSQL
» more
Competitive advantagesBuilt-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
» more
Typical application scenariosTransactional payments applications, reporting and mixed workloads.
» more
Market metricsOver 30 years experience in database technology. Over 20 years in Postgres development...
» more
Licensing and pricing modelsCore based licensing
» more

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More resources
DatabricksFujitsu Enterprise PostgresGoogle BigQuery
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