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DBMS > Amazon DocumentDB vs. Apache Impala vs. CouchDB vs. Datomic vs. Netezza

System Properties Comparison Amazon DocumentDB vs. Apache Impala vs. CouchDB vs. Datomic vs. Netezza

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonApache Impala  Xexclude from comparisonCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"  Xexclude from comparisonDatomic  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceAnalytic DBMS for HadoopA native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityData warehouse and analytics appliance part of IBM PureSystems
Primary database modelDocument storeRelational DBMSDocument storeRelational DBMSRelational DBMS
Secondary database modelsDocument storeSpatial DBMS infousing the Geocouch extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score9.30
Rank#45  Overall
#7  Document stores
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Websiteaws.amazon.com/­documentdbimpala.apache.orgcouchdb.apache.orgwww.datomic.comwww.ibm.com/­products/­netezza
Technical documentationaws.amazon.com/­documentdb/­resourcesimpala.apache.org/­impala-docs.htmldocs.couchdb.org/­en/­stabledocs.datomic.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software Foundation infoApache top-level project, originally developed by Damien Katz, a former Lotus Notes developerCognitectIBM
Initial release20192013200520122000
Current release4.1.0, June 20223.3.3, December 20231.0.6735, June 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open Source infoApache version 2commercial infolimited edition freecommercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ErlangJava, Clojure
Server operating systemshostedLinuxAndroid
BSD
Linux
OS X
Solaris
Windows
All OS with a Java VMLinux infoincluded in appliance
Data schemeschema-freeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesnoyesyes
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.nononono
Secondary indexesyesyesyes infovia viewsyesyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsnonoyes
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBC
ODBC
RESTful HTTP/JSON APIRESTful HTTP APIJDBC
ODBC
OLE DB
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
All languages supporting JDBC/ODBCC
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk
Clojure
Java
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceView functions in JavaScriptyes infoTransaction Functionsyes
TriggersnonoyesBy using transaction functionsno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoimproved architecture with release 2.0none infoBut extensive use of caching in the application peersSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasselectable replication factorMulti-source replication
Source-replica replication
none infoBut extensive use of caching in the application peersSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yes infoquery execution via MapReduceyesnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnono infoatomic operations within a single document possibleACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infostrategy: optimistic lockingyesyes
Durability infoSupport for making data persistentyesyesyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes inforecommended only for testing and development
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users can be defined per databasenoUsers with fine-grained authorization concept

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More resources
Amazon DocumentDBApache ImpalaCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"DatomicNetezza infoAlso called PureData System for Analytics by IBM
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