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DBMS > 4D vs. Atos Standard Common Repository vs. Google Cloud Bigtable vs. IRONdb vs. Tkrzw

System Properties Comparison 4D vs. Atos Standard Common Repository vs. Google Cloud Bigtable vs. IRONdb vs. Tkrzw

Editorial information provided by DB-Engines
Name4D infoformer name: 4th Dimension  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonIRONdb  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionApplication development environment with integrated database management systemHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelRelational DBMSDocument store
Key-value store
Key-value store
Wide column store
Time Series DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.58
Rank#108  Overall
#54  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitewww.4d.comatos.net/en/convergence-creators/portfolio/standard-common-repositorycloud.google.com/­bigtablewww.circonus.com/solutions/time-series-database/dbmx.net/­tkrzw
Technical documentationdeveloper.4d.comcloud.google.com/­bigtable/­docsdocs.circonus.com/irondb/category/getting-started
Developer4D, IncAtos Convergence CreatorsGoogleCirconus LLC.Mikio Hirabayashi
Initial release19842016201520172020
Current releasev20, April 20231703V0.10.20, January 20180.9.3, August 2020
License infoCommercial or Open SourcecommercialcommercialcommercialcommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++C++
Server operating systemsOS X
Windows
LinuxhostedLinuxLinux
macOS
Data schemeyesSchema and schema-less with LDAP viewsschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesoptionalnoyes infotext, numeric, histogramsno
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.yesyesnonono
Secondary indexesyesyesnono
SQL infoSupport of SQLyes infoclose to SQL 92nonoSQL-like query language (Circonus Analytics Query Language: CAQL)no
APIs and other access methodsODBC
RESTful HTTP API infoby using 4D Mobile
SOAP webservices
LDAPgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP API
Supported programming languages4D proprietary IDE
PHP
All languages with LDAP bindingsC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresyesnonoyes, in Luano
Triggersyesyesnonono
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infocell divisionShardingAutomatic, metric affinity per nodenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyesInternal replication in Colossus, and regional replication between two clusters in different zonesconfigurable replication factor, datacenter awarenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate consistency per node, eventual consistency across nodesImmediate Consistency
Foreign keys infoReferential integrityyesnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic execution of specific operationsAtomic single-row operationsno
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.noyesnonoyes infousing specific database classes
User concepts infoAccess controlUsers and groupsLDAP bind authenticationAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nono

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More resources
4D infoformer name: 4th DimensionAtos Standard Common RepositoryGoogle Cloud BigtableIRONdbTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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