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DBMS > Amazon Aurora vs. Faircom EDGE vs. Hazelcast vs. Heroic vs. Microsoft Azure Data Explorer

System Properties Comparison Amazon Aurora vs. Faircom EDGE vs. Hazelcast vs. Heroic vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonHazelcast  Xexclude from comparisonHeroic  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsA widely adopted in-memory data gridTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchFully managed big data interactive analytics platform
Primary database modelRelational DBMSKey-value store
Relational DBMS
Key-value storeTime Series DBMSRelational DBMS infocolumn oriented
Secondary database modelsDocument storeDocument store infoJSON support with IMDG 3.12Document 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
Score7.91
Rank#50  Overall
#32  Relational DBMS
Score0.02
Rank#368  Overall
#54  Key-value stores
#156  Relational DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websiteaws.amazon.com/­rds/­aurorawww.faircom.com/­products/­faircom-edgehazelcast.comgithub.com/­spotify/­heroicazure.microsoft.com/­services/­data-explorer
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmldocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlhazelcast.org/­imdg/­docsspotify.github.io/­heroicdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperAmazonFairCom CorporationHazelcastSpotifyMicrosoft
Initial release20151979200820142019
Current releaseV3, October 20205.3.6, November 2023cloud service with continuous releases
License infoCommercial or Open Sourcecommercialcommercial infoRestricted, free version availableOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageANSI C, C++JavaJava
Server operating systemshostedAndroid
Linux infoARM, x86
Raspbian
Windows
All OS with a Java VMhosted
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freeFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyes, ANSI Standard SQL Typesyesyesyes 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.yesyesyes infothe object must implement a serialization strategynoyes
Secondary indexesyesyesyesyes infovia Elasticsearchall fields are automatically indexed
SQL infoSupport of SQLyesyes infoANSI SQL queriesSQL-like query languagenoKusto Query Language (KQL), SQL subset
APIs and other access methodsADO.NET
JDBC
ODBC
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
JCache
JPA
Memcached protocol
RESTful HTTP API
HQL (Heroic Query Language, a JSON-based language)
HTTP API
Microsoft 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
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresyesyes info.Net, JavaScript, C/C++yes infoEvent Listeners, Executor ServicesnoYes, possible languages: KQL, Python, R
Triggersyesyesyes infoEventsnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningFile partitioning infoCustomizable business rules for partitioningShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes infoSynchronous and asynchronous realtime replication based on transaction logsyes infoReplicated Mapyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Tunable Consistency
Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesyes infowhen using SQLnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDone or two-phase-commit; repeatable reads; read commitednono
Concurrency infoSupport for concurrent manipulation of datayesyes infoacross SQL and NoSQLyesyesyes
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.yesyesyesnono
User concepts infoAccess controlfine grained access rights according to SQL-standardFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Role-based access controlAzure Active Directory Authentication

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More resources
Amazon AuroraFaircom EDGE infoformerly c-treeEDGEHazelcastHeroicMicrosoft Azure Data Explorer
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