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DBMS > Faircom EDGE vs. Fauna vs. Microsoft Azure Data Explorer vs. ObjectBox vs. Teradata

System Properties Comparison Faircom EDGE vs. Fauna vs. Microsoft Azure Data Explorer vs. ObjectBox vs. Teradata

Editorial information provided by DB-Engines
NameFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonFauna infopreviously named FaunaDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonObjectBox  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsFauna 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 platformExtremely fast embedded database for small devices, IoT and MobileA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelKey-value store
Relational DBMS
Document store
Graph DBMS
Relational DBMS
Time Series DBMS
Relational DBMS infocolumn orientedObject oriented DBMSRelational DBMS
Secondary database modelsDocument 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
Time Series DBMSDocument store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.09
Rank#362  Overall
#53  Key-value stores
#155  Relational DBMS
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
Score1.29
Rank#166  Overall
#5  Object oriented DBMS
Score44.87
Rank#22  Overall
#15  Relational DBMS
Websitewww.faircom.com/­products/­faircom-edgefauna.comazure.microsoft.com/­services/­data-explorerobjectbox.iowww.teradata.com
Technical documentationdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmldocs.fauna.comdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.objectbox.iodocs.teradata.com
DeveloperFairCom CorporationFauna, Inc.MicrosoftObjectBox LimitedTeradata
Initial release19792014201920171984
Current releaseV3, October 2020cloud service with continuous releasesTeradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open Sourcecommercial infoRestricted, free version availablecommercialcommercialOpen Source infoApache License 2.0commercial
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageANSI C, C++ScalaC and C++
Server operating systemsAndroid
Linux infoARM, x86
Raspbian
Windows
hostedhostedAndroid
iOS
Linux
macOS
Windows
hosted
Linux
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeFixed schema with schema-less datatypes (dynamic)yesyes
Typing infopredefined data types such as float or dateyes, ANSI Standard SQL Typesnoyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyes
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.yesnoyesnoyes
Secondary indexesyesyesall fields are automatically indexedyesyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLyes infoANSI SQL queriesnoKusto Query Language (KQL), SQL subsetnoyes infoSQL 2016 + extensions
APIs and other access methodsADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
RESTful HTTP APIMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Proprietary native API.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesC
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++user defined functionsYes, possible languages: KQL, Python, Rnoyes infoUDFs, stored procedures, table functions in parallel
Triggersyesnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes
Partitioning methods infoMethods for storing different data on different nodesFile partitioning infoCustomizable business rules for partitioninghorizontal partitioning infoconsistent hashingSharding infoImplicit feature of the cloud servicenoneSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoSynchronous and asynchronous realtime replication based on transaction logsMulti-source replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.online/offline synchronization between client and serverMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Tunable Consistency
Immediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infowhen using SQLyesnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayes infoacross SQL and NoSQLyesyesyesyes
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.yesnononoyes
User concepts infoAccess controlFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Identity management, authentication, and access controlAzure Active Directory Authenticationyesfine grained access rights according to SQL-standard
More information provided by the system vendor
Faircom EDGE infoformerly c-treeEDGEFauna infopreviously named FaunaDBMicrosoft Azure Data ExplorerObjectBoxTeradata
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