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DBMS > Amazon DynamoDB vs. CouchDB vs. Faircom DB vs. RocksDB vs. Splice Machine

System Properties Comparison Amazon DynamoDB vs. CouchDB vs. Faircom DB vs. RocksDB vs. Splice Machine

Editorial information provided by DB-Engines
NameAmazon DynamoDB  Xexclude from comparisonCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonRocksDB  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionHosted, scalable database service by Amazon with the data stored in Amazons cloudA native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Embeddable persistent key-value store optimized for fast storage (flash and RAM)Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument store
Key-value store
Document storeKey-value store
Relational DBMS
Key-value storeRelational DBMS
Secondary database modelsSpatial DBMS infousing the Geocouch extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score74.07
Rank#17  Overall
#3  Document stores
#2  Key-value stores
Score9.30
Rank#45  Overall
#7  Document stores
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Score3.65
Rank#85  Overall
#11  Key-value stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websiteaws.amazon.com/­dynamodbcouchdb.apache.orgwww.faircom.com/­products/­faircom-dbrocksdb.orgsplicemachine.com
Technical documentationdocs.aws.amazon.com/­dynamodbdocs.couchdb.org/­en/­stabledocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlgithub.com/­facebook/­rocksdb/­wikisplicemachine.com/­how-it-works
DeveloperAmazonApache Software Foundation infoApache top-level project, originally developed by Damien Katz, a former Lotus Notes developerFairCom CorporationFacebook, Inc.Splice Machine
Initial release20122005197920132014
Current release3.3.3, December 2023V12, November 20208.11.4, April 20243.1, March 2021
License infoCommercial or Open Sourcecommercial infofree tier for a limited amount of database operationsOpen Source infoApache version 2commercial infoRestricted, free version availableOpen Source infoBSDOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageErlangANSI C, C++C++Java
Server operating systemshostedAndroid
BSD
Linux
OS X
Solaris
Windows
AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
LinuxLinux
OS X
Solaris
Windows
Data schemeschema-freeschema-freeschema free, schema optional, schema required, partial schema,schema-freeyes
Typing infopredefined data types such as float or dateyesnoyes, ANSI SQL Types, JSON, typed binary structuresnoyes
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.nonono
Secondary indexesyesyes infovia viewsyesnoyes
SQL infoSupport of SQLnonoyes, ANSI SQL with proprietary extensionsnoyes
APIs and other access methodsRESTful HTTP APIRESTful HTTP/JSON APIADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
C++ API
Java API
JDBC
Native Spark Datasource
ODBC
Supported programming languages.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby
C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
C
C++
Go
Java
Perl
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoView functions in JavaScriptyes info.Net, JavaScript, C/C++noyes infoJava
Triggersyes infoby integration with AWS Lambdayesyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoimproved architecture with release 2.0File partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioninghorizontal partitioningShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).yesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yesnonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Eventual ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate Consistency
Foreign keys infoReferential integritynonoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoACID across one or more tables within a single AWS account and regionno infoatomic operations within a single document possibletunable from ACID to Eventually ConsistentyesACID
Concurrency infoSupport for concurrent manipulation of datayesyes infostrategy: optimistic lockingyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesYes, tunable from durable to delayed durability to in-memoryyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access rights for users can be defined per databaseFine grained access rights according to SQL-standard with additional protections for filesnoAccess rights for users, groups and roles according to SQL-standard

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More resources
Amazon DynamoDBCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"Faircom DB infoformerly c-treeACERocksDBSplice Machine
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