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DBMS > Faircom DB vs. Microsoft Azure Data Explorer vs. Oracle vs. Solr

System Properties Comparison Faircom DB vs. Microsoft Azure Data Explorer vs. Oracle vs. Solr

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Editorial information provided by DB-Engines
NameFaircom DB infoformerly c-treeACE  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOracle  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Fully managed big data interactive analytics platformWidely used RDBMSA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelKey-value store
Relational DBMS
Relational DBMS infocolumn orientedRelational DBMSSearch engine
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
Document store
Graph DBMS infowith Oracle Spatial and Graph
RDF store infowith Oracle Spatial and Graph
Spatial DBMS infowith Oracle Spatial and Graph
Vector DBMS infosince Oracle 23
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.29
Rank#304  Overall
#43  Key-value stores
#136  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score1244.08
Rank#1  Overall
#1  Relational DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Websitewww.faircom.com/­products/­faircom-dbazure.microsoft.com/­services/­data-explorerwww.oracle.com/­databasesolr.apache.org
Technical documentationdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmldocs.microsoft.com/­en-us/­azure/­data-explorerdocs.oracle.com/­en/­databasesolr.apache.org/­resources.html
DeveloperFairCom CorporationMicrosoftOracleApache Software Foundation
Initial release1979201919802006
Current releaseV12, November 2020cloud service with continuous releases23c, September 20239.6.1, May 2024
License infoCommercial or Open Sourcecommercial infoRestricted, free version availablecommercialcommercial inforestricted free version is availableOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageANSI C, C++C and C++Java
Server operating systemsAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
hostedAIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema free, schema optional, schema required, partial schema,Fixed schema with schema-less datatypes (dynamic)yes infoSchemaless in JSON and XML columnsyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyes, ANSI SQL Types, JSON, typed binary structuresyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyes infosupports customizable data types and automatic typing
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.noyesyesyes
Secondary indexesyesall fields are automatically indexedyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLyes, ANSI SQL with proprietary extensionsKusto Query Language (KQL), SQL subsetyes infowith proprietary extensionsSolr Parallel SQL Interface
APIs and other access methodsADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Java API
RESTful HTTP/JSON API
Supported programming languages.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++Yes, possible languages: KQL, Python, RPL/SQL infoalso stored procedures in Java possibleJava plugins
Triggersyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningSharding infoImplicit feature of the cloud serviceSharding, horizontal partitioningSharding
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).yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
Source-replica replication
yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno infocan be realized in PL/SQLspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Eventual Consistency
Immediate Consistency
Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datatunable from ACID to Eventually ConsistentnoACID infoisolation level can be parameterizedoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentYes, tunable from durable to delayed durability to in-memoryyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infoVersion 12c introduced the new option 'Oracle Database In-Memory'yes
User concepts infoAccess controlFine grained access rights according to SQL-standard with additional protections for filesAzure Active Directory Authenticationfine grained access rights according to SQL-standardyes

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More resources
Faircom DB infoformerly c-treeACEMicrosoft Azure Data ExplorerOracleSolr
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Oracle Cloud World
Las Vegas, 9-12 September 2024

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