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DBMS > Datomic vs. Faircom EDGE vs. Fauna vs. IBM Db2 vs. Microsoft Azure Data Explorer

System Properties Comparison Datomic vs. Faircom EDGE vs. Fauna vs. IBM Db2 vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonFauna infopreviously named FaunaDB  Xexclude from comparisonIBM Db2 infoformerly named DB2 or IBM Database 2  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityFairCom 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.Common in IBM host environments, 2 different versions for host and Windows/LinuxFully managed big data interactive analytics platform
Primary database modelRelational DBMSKey-value store
Relational DBMS
Document store
Graph DBMS
Relational DBMS
Time Series DBMS
Relational DBMS infoSince Version 10.5 support for JSON/BSON documents compatible with MongoDBRelational DBMS infocolumn oriented
Secondary database modelsDocument store
RDF store infoin Db2 LUW (Linux, Unix, Windows)
Spatial DBMS infowith Db2 Spatial Extender
Document 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
Score1.66
Rank#144  Overall
#66  Relational DBMS
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
Score125.90
Rank#9  Overall
#6  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websitewww.datomic.comwww.faircom.com/­products/­faircom-edgefauna.comwww.ibm.com/­products/­db2azure.microsoft.com/­services/­data-explorer
Technical documentationdocs.datomic.comdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmldocs.fauna.comwww.ibm.com/­docs/­en/­db2docs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperCognitectFairCom CorporationFauna, Inc.IBMMicrosoft
Initial release2012197920141983 infohost version2019
Current release1.0.6735, June 2023V3, October 202012.1, October 2016cloud service with continuous releases
License infoCommercial or Open Sourcecommercial infolimited edition freecommercial infoRestricted, free version availablecommercialcommercial infofree version is availablecommercial
Cloud-based only infoOnly available as a cloud servicenonoyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureANSI C, C++ScalaC and C++
Server operating systemsAll OS with a Java VMAndroid
Linux infoARM, x86
Raspbian
Windows
hostedAIX
HP-UX
Linux
Solaris
Windows
z/OS
hosted
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-freeyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyes, ANSI Standard SQL Typesnoyesyes 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.noyesnoyes
Secondary indexesyesyesyesyesall fields are automatically indexed
SQL infoSupport of SQLnoyes infoANSI SQL queriesnoyesKusto Query Language (KQL), SQL subset
APIs and other access methodsRESTful HTTP APIADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
RESTful HTTP APIADO.NET
JDBC
JSON style queries infoMongoDB compatible
ODBC
XQuery
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesClojure
Java
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift
C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresyes infoTransaction Functionsyes info.Net, JavaScript, C/C++user defined functionsyesYes, possible languages: KQL, Python, R
TriggersBy using transaction functionsyesnoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersFile partitioning infoCustomizable business rules for partitioninghorizontal partitioning infoconsistent hashingSharding infoonly with Windows/Unix/Linux VersionSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersyes infoSynchronous and asynchronous realtime replication based on transaction logsMulti-source replicationyes infowith separate tools (MQ, InfoSphere)yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Tunable Consistency
Immediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes infowhen using SQLyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes infoacross SQL and NoSQLyesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentyesnono
User concepts infoAccess controlnoFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Identity management, authentication, and access controlfine grained access rights according to SQL-standardAzure Active Directory Authentication

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More resources
DatomicFaircom EDGE infoformerly c-treeEDGEFauna infopreviously named FaunaDBIBM Db2 infoformerly named DB2 or IBM Database 2Microsoft Azure Data Explorer
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