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DBMS > Amazon Aurora vs. Apache Impala vs. CouchDB vs. Fauna vs. Microsoft Azure Data Explorer

System Properties Comparison Amazon Aurora vs. Apache Impala vs. CouchDB vs. Fauna vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonApache Impala  Xexclude from comparisonCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"  Xexclude from comparisonFauna infopreviously named FaunaDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonAnalytic DBMS for HadoopA native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.Fully managed big data interactive analytics platform
Primary database modelRelational DBMSRelational DBMSDocument storeDocument store
Graph DBMS
Relational DBMS
Time Series DBMS
Relational DBMS infocolumn oriented
Secondary database modelsDocument storeDocument storeSpatial DBMS infousing the Geocouch extensionDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.57
Rank#51  Overall
#32  Relational DBMS
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score8.30
Rank#47  Overall
#7  Document stores
Score1.55
Rank#151  Overall
#26  Document stores
#14  Graph DBMS
#71  Relational DBMS
#13  Time Series DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websiteaws.amazon.com/­rds/­auroraimpala.apache.orgcouchdb.apache.orgfauna.comazure.microsoft.com/­services/­data-explorer
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlimpala.apache.org/­impala-docs.htmldocs.couchdb.org/­en/­stabledocs.fauna.comdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperAmazonApache 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 developerFauna, Inc.Microsoft
Initial release20152013200520142019
Current release4.1.0, June 20223.3.3, December 2023cloud service with continuous releases
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open Source infoApache version 2commercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnonoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++ErlangScala
Server operating systemshostedLinuxAndroid
BSD
Linux
OS X
Solaris
Windows
hostedhosted
Data schemeyesyesschema-freeschema-freeFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyesnonoyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types
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.yesnononoyes
Secondary indexesyesyesyes infovia viewsyesall fields are automatically indexed
SQL infoSupport of SQLyesSQL-like DML and DDL statementsnonoKusto Query Language (KQL), SQL subset
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
RESTful HTTP/JSON APIRESTful HTTP APIMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
All languages supporting JDBC/ODBCC
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk
C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresyesyes infouser defined functions and integration of map-reduceView functions in JavaScriptuser defined functionsYes, possible languages: KQL, Python, R
Triggersyesnoyesnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingSharding infoimproved architecture with release 2.0horizontal partitioning infoconsistent hashingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factorMulti-source replication
Source-replica replication
Multi-source replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono infoatomic operations within a single document possibleACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes infostrategy: optimistic lockingyesyes
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.yesnononono
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users can be defined per databaseIdentity management, authentication, and access controlAzure Active Directory Authentication

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More resources
Amazon AuroraApache ImpalaCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"Fauna infopreviously named FaunaDBMicrosoft Azure Data Explorer
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