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DBMS > Amazon Aurora vs. Databricks vs. Fujitsu Enterprise Postgres vs. Google Cloud Spanner

System Properties Comparison Amazon Aurora vs. Databricks vs. Fujitsu Enterprise Postgres vs. Google Cloud Spanner

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonDatabricks  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonThe 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.A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.
Primary database modelRelational DBMSDocument store
Relational DBMS
Relational DBMSRelational DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.57
Rank#51  Overall
#32  Relational DBMS
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.37
Rank#278  Overall
#128  Relational DBMS
Score2.84
Rank#100  Overall
#51  Relational DBMS
Websiteaws.amazon.com/­rds/­aurorawww.databricks.comwww.postgresql.fastware.comcloud.google.com/­spanner
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmldocs.databricks.comwww.postgresql.fastware.com/­product-manualscloud.google.com/­spanner/­docs
DeveloperAmazonDatabricksPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyGoogle
Initial release201520132017
Current releaseFujitsu Enterprise Postgres 14, January 2022
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC
Server operating systemshostedhostedLinux
Windows
hosted
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesyes
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.yesyesno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyeswith Databricks SQLyesyes infoQuery statements complying to ANSI 2011
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Python
R
Scala
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyesuser defined functions and aggregatesuser defined functionsno
Triggersyesyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningpartitioning by range, list and by hashSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesSource-replica replicationMulti-source replication with 3 replicas for regional instances.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrity
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID infoStrict serializable isolation
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)
More information provided by the system vendor
Amazon AuroraDatabricksFujitsu Enterprise PostgresGoogle Cloud Spanner
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Amazon AuroraDatabricksFujitsu Enterprise PostgresGoogle Cloud Spanner
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