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DBMS > 4D vs. Google Cloud Datastore vs. Postgres-XL vs. Spark SQL vs. UniData,UniVerse

System Properties Comparison 4D vs. Google Cloud Datastore vs. Postgres-XL vs. Spark SQL vs. UniData,UniVerse

Editorial information provided by DB-Engines
Name4D infoformer name: 4th Dimension  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonPostgres-XL  Xexclude from comparisonSpark SQL  Xexclude from comparisonUniData,UniVerse  Xexclude from comparison
DescriptionApplication development environment with integrated database management systemAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresSpark SQL is a component on top of 'Spark Core' for structured data processingMultiValue database and application server with SQL mapping layer and meta database capabilities
Primary database modelRelational DBMSDocument storeRelational DBMSRelational DBMSMultivalue DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.58
Rank#108  Overall
#54  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score0.49
Rank#256  Overall
#117  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score3.16
Rank#97  Overall
#2  Multivalue DBMS
Websitewww.4d.comcloud.google.com/­datastorewww.postgres-xl.orgspark.apache.org/­sqlwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-unidata
Technical documentationdeveloper.4d.comcloud.google.com/­datastore/­docswww.postgres-xl.org/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.rocketsoftware.com/­bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata
Developer4D, IncGoogleApache Software FoundationRocket Software
Initial release198420082014 infosince 2012, originally named StormDB20141985
Current releasev20, April 202310 R1, October 20183.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoMozilla public licenseOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCScalaC
Server operating systemsOS X
Windows
hostedLinux
macOS
Linux
OS X
Windows
AIX
HP-UX
Linux
Solaris
Windows
Data schemeyesschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyesyes, details hereyesyesoptional
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.yesnoyes infoXML type, but no XML query functionalityno
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLyes infoclose to SQL 92SQL-like query language (GQL)yes infodistributed, parallel query executionSQL-like DML and DDL statementsyes
APIs and other access methodsODBC
RESTful HTTP API infoby using 4D Mobile
SOAP webservices
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Java API infoJPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API
Supported programming languages4D proprietary IDE
PHP
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Java
Python
R
Scala
.Net
Basic infoU2 Basic
C
Java
Server-side scripts infoStored proceduresyesusing Google App Engineuser defined functionsnoyes
TriggersyesCallbacks using the Google Apps Engineyesnoyes infoU2 Basic
Partitioning methods infoMethods for storing different data on different nodesnoneShardinghorizontal partitioningyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationMulti-source replication using PaxosnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID infoMVCCnoACID infoconfigurable
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.nononono
User concepts infoAccess controlUsers and groupsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardnoAccess rights according to SQL-standard and operating system based

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More resources
4D infoformer name: 4th DimensionGoogle Cloud DatastorePostgres-XLSpark SQLUniData,UniVerse
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