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

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

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonApache Impala  Xexclude from comparisonFauna infopreviously named FaunaDB  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonAnalytic DBMS for HadoopFauna 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.A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineFully managed big data interactive analytics platform
Primary database modelRelational DBMSRelational DBMSDocument store
Graph DBMS
Relational DBMS
Time Series DBMS
Graph DBMS
Key-value store
Relational DBMS infocolumn oriented
Secondary database modelsDocument storeDocument storeDocument 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
Score1.55
Rank#151  Overall
#26  Document stores
#14  Graph DBMS
#71  Relational DBMS
#13  Time Series DBMS
Score0.67
Rank#232  Overall
#21  Graph DBMS
#34  Key-value stores
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websiteaws.amazon.com/­rds/­auroraimpala.apache.orgfauna.comwww.graphengine.ioazure.microsoft.com/­services/­data-explorer
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlimpala.apache.org/­impala-docs.htmldocs.fauna.comwww.graphengine.io/­docs/­manualdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperAmazonApache Software Foundation infoApache top-level project, originally developed by ClouderaFauna, Inc.MicrosoftMicrosoft
Initial release20152013201420102019
Current release4.1.0, June 2022cloud service with continuous releases
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercialOpen Source infoMIT Licensecommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Scala.NET and C
Server operating systemshostedLinuxhosted.NEThosted
Data schemeyesyesschema-freeyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyesnoyesyes 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 indexesyesyesyesall 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 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#
Go
Java
JavaScript
Python
Ruby
Scala
Swift
C#
C++
F#
Visual Basic
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresyesyes infouser defined functions and integration of map-reduceuser defined functionsyesYes, possible languages: KQL, Python, R
Triggersyesnononoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardinghorizontal partitioning infoconsistent hashinghorizontal partitioningSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factorMulti-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 MapReducenoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles infobased on Apache Sentry and KerberosIdentity management, authentication, and access controlAzure Active Directory Authentication

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More resources
Amazon AuroraApache ImpalaFauna infopreviously named FaunaDBGraph Engine infoformer name: TrinityMicrosoft Azure Data Explorer
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