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DBMS > 4D vs. Apache IoTDB vs. Brytlyt vs. CouchDB vs. Google Cloud Bigtable

System Properties Comparison 4D vs. Apache IoTDB vs. Brytlyt vs. CouchDB vs. Google Cloud Bigtable

Editorial information provided by DB-Engines
Name4D infoformer name: 4th Dimension  Xexclude from comparisonApache IoTDB  Xexclude from comparisonBrytlyt  Xexclude from comparisonCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparison
DescriptionApplication development environment with integrated database management systemAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLA native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.
Primary database modelRelational DBMSTime Series DBMSRelational DBMSDocument storeKey-value store
Wide column store
Secondary database modelsSpatial DBMS infousing the Geocouch extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.47
Rank#110  Overall
#54  Relational DBMS
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.38
Rank#276  Overall
#127  Relational DBMS
Score8.30
Rank#47  Overall
#7  Document stores
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Websitewww.4d.comiotdb.apache.orgbrytlyt.iocouchdb.apache.orgcloud.google.com/­bigtable
Technical documentationdeveloper.4d.comiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.brytlyt.iodocs.couchdb.org/­en/­stablecloud.google.com/­bigtable/­docs
Developer4D, IncApache Software FoundationBrytlytApache Software Foundation infoApache top-level project, originally developed by Damien Katz, a former Lotus Notes developerGoogle
Initial release19842018201620052015
Current releasev20, April 20231.1.0, April 20235.0, August 20233.3.3, December 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialOpen Source infoApache version 2commercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++ and CUDAErlang
Server operating systemsOS X
Windows
All OS with a Java VM (>= 1.8)Linux
OS X
Windows
Android
BSD
Linux
OS X
Solaris
Windows
hosted
Data schemeyesyesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyesnono
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 infospecific XML-type available, but no XML query functionality.nono
Secondary indexesyesyesyesyes infovia viewsno
SQL infoSupport of SQLyes infoclose to SQL 92SQL-like query languageyesnono
APIs and other access methodsODBC
RESTful HTTP API infoby using 4D Mobile
SOAP webservices
JDBC
Native API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
RESTful HTTP/JSON APIgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Supported programming languages4D proprietary IDE
PHP
C
C#
C++
Go
Java
Python
Scala
.Net
C
C++
Delphi
Java
Perl
Python
Tcl
C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk
C#
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyesyesuser defined functions infoin PL/pgSQLView functions in JavaScriptno
Triggersyesyesyesyesno
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding infoimproved architecture with release 2.0Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasSource-replica replicationMulti-source replication
Source-replica replication
Internal replication in Colossus, and regional replication between two clusters in different zones
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoIntegration with Hadoop and Sparknoyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyEventual ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integrityyesnoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDno infoatomic operations within a single document possibleAtomic single-row operations
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infostrategy: optimistic lockingyes
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 groupsyesfine grained access rights according to SQL-standardAccess rights for users can be defined per databaseAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
4D infoformer name: 4th DimensionApache IoTDBBrytlytCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"Google Cloud Bigtable
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