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DBMS > Faircom DB vs. Infobright vs. Microsoft Azure Data Explorer vs. Postgres-XL vs. SAP SQL Anywhere

System Properties Comparison Faircom DB vs. Infobright vs. Microsoft Azure Data Explorer vs. Postgres-XL vs. SAP SQL Anywhere

Editorial information provided by DB-Engines
NameFaircom DB infoformerly c-treeACE  Xexclude from comparisonInfobright  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonPostgres-XL  Xexclude from comparisonSAP SQL Anywhere infoformerly called Adaptive Server Anywhere  Xexclude from comparison
DescriptionNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontendFully managed big data interactive analytics platformBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresRDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments
Primary database modelKey-value store
Relational DBMS
Relational DBMSRelational DBMS infocolumn orientedRelational 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
Document store
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
Score1.02
Rank#192  Overall
#90  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.53
Rank#254  Overall
#117  Relational DBMS
Score3.95
Rank#80  Overall
#42  Relational DBMS
Websitewww.faircom.com/­products/­faircom-dbignitetech.com/­softwarelibrary/­infobrightdbazure.microsoft.com/­services/­data-explorerwww.postgres-xl.orgwww.sap.com/­products/­technology-platform/­sql-anywhere.html
Technical documentationdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmldocs.microsoft.com/­en-us/­azure/­data-explorerwww.postgres-xl.org/­documentationhelp.sap.com/­docs/­SAP_SQL_Anywhere
DeveloperFairCom CorporationIgnite Technologies Inc.; formerly InfoBright Inc.MicrosoftSAP infoformerly Sybase
Initial release1979200520192014 infosince 2012, originally named StormDB1992
Current releaseV12, November 2020cloud service with continuous releases10 R1, October 201817, July 2015
License infoCommercial or Open Sourcecommercial infoRestricted, free version availablecommercial infoThe open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016commercialOpen Source infoMozilla public licensecommercial
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageANSI C, C++CC
Server operating systemsAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Linux
Windows
hostedLinux
macOS
AIX
HP-UX
Linux
OS X
Solaris
Windows
Data schemeschema free, schema optional, schema required, partial schema,yesFixed schema with schema-less datatypes (dynamic)yesyes
Typing infopredefined data types such as float or dateyes, ANSI SQL Types, JSON, typed binary structuresyesyes 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.nonoyesyes infoXML type, but no XML query functionalityyes
Secondary indexesyesno infoKnowledge Grid Technology used insteadall fields are automatically indexedyesyes
SQL infoSupport of SQLyes, ANSI SQL with proprietary extensionsyesKusto Query Language (KQL), SQL subsetyes infodistributed, parallel query executionyes
APIs and other access methodsADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
ADO.NET
JDBC
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
HTTP API
JDBC
ODBC
Supported programming languages.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++noYes, possible languages: KQL, Python, Ruser defined functionsyes, in C/C++, Java, .Net or Perl
Triggersyesnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesyes
Partitioning methods infoMethods for storing different data on different nodesFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningnoneSharding infoImplicit feature of the cloud servicehorizontal partitioningnone
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).Source-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication infoDatabase mirroring
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 systemEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datatunable from ACID to Eventually ConsistentACIDnoACID infoMVCCACID
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.yesyesnonoyes
User concepts infoAccess controlFine grained access rights according to SQL-standard with additional protections for filesfine grained access rights according to SQL-standard infoexploiting MySQL or PostgreSQL frontend capabilitiesAzure Active Directory Authenticationfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Faircom DB infoformerly c-treeACEInfobrightMicrosoft Azure Data ExplorerPostgres-XLSAP SQL Anywhere infoformerly called Adaptive Server Anywhere
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