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DBMS > Faircom DB vs. Microsoft Azure Data Explorer vs. OpenQM vs. SAP SQL Anywhere vs. Splice Machine

System Properties Comparison Faircom DB vs. Microsoft Azure Data Explorer vs. OpenQM vs. SAP SQL Anywhere vs. Splice Machine

Editorial information provided by DB-Engines
NameFaircom DB infoformerly c-treeACE  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOpenQM infoalso called QM  Xexclude from comparisonSAP SQL Anywhere infoformerly called Adaptive Server Anywhere  Xexclude from comparisonSplice Machine  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 platformQpenQM is a high-performance, self-tuning, multi-value DBMSRDBMS database and synchronization technologies for server, desktop, remote office, and mobile environmentsOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelKey-value store
Relational DBMS
Relational DBMS infocolumn orientedMultivalue DBMSRelational 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
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
Score0.34
Rank#284  Overall
#10  Multivalue DBMS
Score3.95
Rank#80  Overall
#42  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitewww.faircom.com/­products/­faircom-dbazure.microsoft.com/­services/­data-explorerwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-open-qmwww.sap.com/­products/­technology-platform/­sql-anywhere.htmlsplicemachine.com
Technical documentationdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmldocs.microsoft.com/­en-us/­azure/­data-explorerhelp.sap.com/­docs/­SAP_SQL_Anywheresplicemachine.com/­how-it-works
DeveloperFairCom CorporationMicrosoftRocket Software, originally Martin PhillipsSAP infoformerly SybaseSplice Machine
Initial release19792019199319922014
Current releaseV12, November 2020cloud service with continuous releases3.4-1217, July 20153.1, March 2021
License infoCommercial or Open Sourcecommercial infoRestricted, free version availablecommercialOpen Source infoGPLv2, extended commercial license availablecommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageANSI C, C++Java
Server operating systemsAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
hostedAIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows
AIX
HP-UX
Linux
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeschema free, schema optional, schema required, partial schema,Fixed schema with schema-less datatypes (dynamic)yes infowith some exceptionsyesyes
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
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 indexedyesyesyes
SQL infoSupport of SQLyes, ANSI SQL with proprietary extensionsKusto Query Language (KQL), SQL subsetnoyesyes
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
ADO.NET
HTTP API
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
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
.Net
Basic
C
Java
Objective C
PHP
Python
C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++Yes, possible languages: KQL, Python, Ryesyes, in C/C++, Java, .Net or Perlyes infoJava
Triggersyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesyesyes
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 serviceyesnoneShared Nothhing Auto-Sharding, Columnar Partitioning
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.yesSource-replica replication infoDatabase mirroringMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknonoYes, via Full Spark Integration
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 ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datatunable from ACID to Eventually ConsistentnoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
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.yesnoyesyes
User concepts infoAccess controlFine grained access rights according to SQL-standard with additional protections for filesAzure Active Directory AuthenticationAccess rights can be defined down to the item levelfine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standard

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More resources
Faircom DB infoformerly c-treeACEMicrosoft Azure Data ExplorerOpenQM infoalso called QMSAP SQL Anywhere infoformerly called Adaptive Server AnywhereSplice Machine
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