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DBMS > Atos Standard Common Repository vs. Faircom DB vs. Fauna vs. Microsoft Azure Data Explorer

System Properties Comparison Atos Standard Common Repository vs. Faircom DB vs. Fauna vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonFauna infopreviously named FaunaDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.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 modelDocument store
Key-value store
Key-value store
Relational DBMS
Document store
Graph DBMS
Relational DBMS
Time Series DBMS
Relational DBMS infocolumn oriented
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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.18
Rank#314  Overall
#45  Key-value stores
#141  Relational DBMS
Score1.55
Rank#143  Overall
#26  Document stores
#13  Graph DBMS
#66  Relational DBMS
#13  Time Series DBMS
Score3.28
Rank#83  Overall
#45  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.faircom.com/­products/­faircom-dbfauna.comazure.microsoft.com/­services/­data-explorer
Technical documentationdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmldocs.fauna.comdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperAtos Convergence CreatorsFairCom CorporationFauna, Inc.Microsoft
Initial release2016197920142019
Current release1703V13, July 2024cloud service with continuous releases
License infoCommercial or Open Sourcecommercialcommercial infoRestricted, free version availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaANSI C, C++Scala
Server operating systemsLinuxAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
hostedhosted
Data schemeSchema and schema-less with LDAP viewsschema free, schema optional, schema required, partial schema,schema-freeFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateoptionalyes, ANSI SQL Types, JSON, typed binary structuresnoyes 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.yesnonoyes
Secondary indexesyesyesyesall fields are automatically indexed
SQL infoSupport of SQLnoyes, ANSI SQL with proprietary extensionsnoKusto Query Language (KQL), SQL subset
APIs and other access methodsLDAPADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
RESTful HTTP APIMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesAll languages with LDAP bindings.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresnoyes info.Net, JavaScript, C/C++user defined functionsYes, possible languages: KQL, Python, R
Triggersyesyesnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioninghorizontal partitioning infoconsistent hashingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).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 methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationstunable from ACID to Eventually ConsistentACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesYes, tunable from durable to delayed durability to in-memoryyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnono
User concepts infoAccess controlLDAP bind authenticationFine grained access rights according to SQL-standard with additional protections for filesIdentity management, authentication, and access controlAzure Active Directory Authentication

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More resources
Atos Standard Common RepositoryFaircom DB infoformerly c-treeACEFauna infopreviously named FaunaDBMicrosoft Azure Data Explorer
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