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DBMS > 4D vs. BigObject vs. EsgynDB vs. Google Cloud Bigtable vs. MonetDB

System Properties Comparison 4D vs. BigObject vs. EsgynDB vs. Google Cloud Bigtable vs. MonetDB

Editorial information provided by DB-Engines
Name4D infoformer name: 4th Dimension  Xexclude from comparisonBigObject  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonMonetDB  Xexclude from comparison
DescriptionApplication development environment with integrated database management systemAnalytic DBMS for real-time computations and queriesEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A relational database management system that stores data in columns
Primary database modelRelational DBMSRelational DBMS infoa hierachical model (tree) can be imposedRelational DBMSKey-value store
Wide column store
Relational 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
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score1.72
Rank#145  Overall
#67  Relational DBMS
Websitewww.4d.combigobject.iowww.esgyn.cncloud.google.com/­bigtablewww.monetdb.org
Technical documentationdeveloper.4d.comdocs.bigobject.iocloud.google.com/­bigtable/­docswww.monetdb.org/­Documentation
Developer4D, IncBigObject, Inc.EsgynGoogleMonetDB BV
Initial release19842015201520152004
Current releasev20, April 2023Dec2023 (11.49), December 2023
License infoCommercial or Open Sourcecommercialcommercial infofree community edition availablecommercialcommercialOpen Source infoMozilla Public License 2.0
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaC
Server operating systemsOS X
Windows
Linux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
LinuxhostedFreeBSD
Linux
OS X
Solaris
Windows
Data schemeyesyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesnoyes
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.yesnonono
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLyes infoclose to SQL 92SQL-like DML and DDL statementsyesnoyes infoSQL 2003 with some extensions
APIs and other access methodsODBC
RESTful HTTP API infoby using 4D Mobile
SOAP webservices
fluentd
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
Supported programming languages4D proprietary IDE
PHP
All languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Server-side scripts infoStored proceduresyesLuaJava Stored Proceduresnoyes, in SQL, C, R
Triggersyesnononoyes
Partitioning methods infoMethods for storing different data on different nodesnonenoneShardingShardingSharding via remote tables
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationnoneMulti-source replication between multi datacentersInternal replication in Colossus, and regional replication between two clusters in different zonesnone infoSource-replica replication available in experimental status
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integrityyesyes infoautomatically between fact table and dimension tablesyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDAtomic single-row operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/write lock on objects (tables, trees)yesyesyes
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.noyesnono
User concepts infoAccess controlUsers and groupsnofine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standard

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More resources
4D infoformer name: 4th DimensionBigObjectEsgynDBGoogle Cloud BigtableMonetDB
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