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DBMS > Amazon Neptune vs. BigObject vs. CouchDB vs. IRONdb vs. Tkrzw

System Properties Comparison Amazon Neptune vs. BigObject vs. CouchDB vs. IRONdb vs. Tkrzw

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonBigObject  Xexclude from comparisonCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"  Xexclude from comparisonIRONdb  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionFast, reliable graph database built for the cloudAnalytic DBMS for real-time computations and queriesA native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.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 modelGraph DBMS
RDF store
Relational DBMS infoa hierachical model (tree) can be imposedDocument storeTime Series DBMSKey-value store
Secondary database modelsSpatial DBMS infousing the Geocouch extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.20
Rank#119  Overall
#9  Graph DBMS
#5  RDF stores
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score9.30
Rank#45  Overall
#7  Document stores
Score0.00
Rank#383  Overall
#60  Key-value stores
Websiteaws.amazon.com/­neptunebigobject.iocouchdb.apache.orgwww.circonus.com/solutions/time-series-database/dbmx.net/­tkrzw
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.bigobject.iodocs.couchdb.org/­en/­stabledocs.circonus.com/irondb/category/getting-started
DeveloperAmazonBigObject, Inc.Apache Software Foundation infoApache top-level project, originally developed by Damien Katz, a former Lotus Notes developerCirconus LLC.Mikio Hirabayashi
Initial release20172015200520172020
Current release3.3.3, December 2023V0.10.20, January 20180.9.3, August 2020
License infoCommercial or Open Sourcecommercialcommercial infofree community edition availableOpen Source infoApache version 2commercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageErlangC and C++C++
Server operating systemshostedLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
Android
BSD
Linux
OS X
Solaris
Windows
LinuxLinux
macOS
Data schemeschema-freeyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesnoyes 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.nonononono
Secondary indexesnoyesyes infovia viewsno
SQL infoSupport of SQLnoSQL-like DML and DDL statementsnoSQL-like query language (Circonus Analytics Query Language: CAQL)no
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
fluentd
ODBC
RESTful HTTP API
RESTful HTTP/JSON APIHTTP API
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk
.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 proceduresnoLuaView functions in JavaScriptyes, in Luano
Triggersnonoyesnono
Partitioning methods infoMethods for storing different data on different nodesnonenoneSharding infoimproved architecture with release 2.0Automatic, metric affinity per nodenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.noneMulti-source replication
Source-replica replication
configurable replication factor, datacenter awarenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneEventual ConsistencyImmediate consistency per node, eventual consistency across nodesImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsyes infoautomatically between fact table and dimension tablesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono infoatomic operations within a single document possibleno
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/write lock on objects (tables, trees)yes infostrategy: optimistic lockingyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes infousing specific database classes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)noAccess rights for users can be defined per databasenono

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Amazon NeptuneBigObjectCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"IRONdbTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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