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DBMS > Faircom DB vs. Fauna vs. Microsoft Azure Data Explorer vs. Netezza vs. OrientDB

System Properties Comparison Faircom DB vs. Fauna vs. Microsoft Azure Data Explorer vs. Netezza vs. OrientDB

Editorial information provided by DB-Engines
NameFaircom DB infoformerly c-treeACE  Xexclude from comparisonFauna infopreviously named FaunaDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonOrientDB  Xexclude from comparison
DescriptionNative 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 platformData warehouse and analytics appliance part of IBM PureSystemsMulti-model DBMS (Document, Graph, Key/Value)
Primary database modelKey-value store
Relational DBMS
Document store
Graph DBMS
Relational DBMS
Time Series DBMS
Relational DBMS infocolumn orientedRelational DBMSDocument store
Graph DBMS
Key-value store
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
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Score1.52
Rank#153  Overall
#26  Document stores
#14  Graph DBMS
#71  Relational DBMS
#13  Time Series DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score3.19
Rank#93  Overall
#16  Document stores
#7  Graph DBMS
#14  Key-value stores
Websitewww.faircom.com/­products/­faircom-dbfauna.comazure.microsoft.com/­services/­data-explorerwww.ibm.com/­products/­netezzaorientdb.org
Technical documentationdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmldocs.fauna.comdocs.microsoft.com/­en-us/­azure/­data-explorerwww.orientdb.com/­docs/­last/­index.html
DeveloperFairCom CorporationFauna, Inc.MicrosoftIBMOrientDB LTD; CallidusCloud; SAP
Initial release19792014201920002010
Current releaseV12, November 2020cloud service with continuous releases3.2.29, March 2024
License infoCommercial or Open Sourcecommercial infoRestricted, free version availablecommercialcommercialcommercialOpen Source infoApache version 2
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageANSI C, C++ScalaJava
Server operating systemsAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
hostedhostedLinux infoincluded in applianceAll OS with a Java JDK (>= JDK 6)
Data schemeschema free, schema optional, schema required, partial schema,schema-freeFixed schema with schema-less datatypes (dynamic)yesschema-free infoSchema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")
Typing infopredefined data types such as float or dateyes, 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-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.nonoyesno
Secondary indexesyesyesall fields are automatically indexedyesyes
SQL infoSupport of SQLyes, ANSI SQL with proprietary extensionsnoKusto Query Language (KQL), SQL subsetyesSQL-like query language, no joins
APIs and other access methodsADO.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
JDBC
ODBC
OLE DB
Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API
Supported programming languages.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
C
C++
Fortran
Java
Lua
Perl
Python
R
.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++user defined functionsYes, possible languages: KQL, Python, RyesJava, Javascript
Triggersyesnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoHooks
Partitioning methods infoMethods for storing different data on different nodesFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioninghorizontal partitioning infoconsistent hashingSharding infoImplicit feature of the cloud serviceShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, 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.Source-replica replicationMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyesno infocould be achieved with distributed queries
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesyesnonoyes inforelationship in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datatunable from ACID to Eventually ConsistentACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentYes, tunable from durable to delayed durability to in-memoryyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlFine grained access rights according to SQL-standard with additional protections for filesIdentity management, authentication, and access controlAzure Active Directory AuthenticationUsers with fine-grained authorization conceptAccess rights for users and roles; record level security configurable

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More resources
Faircom DB infoformerly c-treeACEFauna infopreviously named FaunaDBMicrosoft Azure Data ExplorerNetezza infoAlso called PureData System for Analytics by IBMOrientDB
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