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DBMS > EXASOL vs. Faircom DB vs. Faircom EDGE vs. Microsoft Azure Data Explorer vs. SiteWhere

System Properties Comparison EXASOL vs. Faircom DB vs. Faircom EDGE vs. Microsoft Azure Data Explorer vs. SiteWhere

Editorial information provided by DB-Engines
NameEXASOL  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSiteWhere  Xexclude from comparison
DescriptionHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsFully managed big data interactive analytics platformM2M integration platform for persisting/querying time series data
Primary database modelRelational DBMSKey-value store
Relational DBMS
Key-value store
Relational DBMS
Relational DBMS infocolumn orientedTime Series 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
Score1.76
Rank#139  Overall
#62  Relational DBMS
Score0.29
Rank#304  Overall
#43  Key-value stores
#136  Relational DBMS
Score0.09
Rank#362  Overall
#53  Key-value stores
#155  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.06
Rank#383  Overall
#43  Time Series DBMS
Websitewww.exasol.comwww.faircom.com/­products/­faircom-dbwww.faircom.com/­products/­faircom-edgeazure.microsoft.com/­services/­data-explorergithub.com/­sitewhere/­sitewhere
Technical documentationwww.exasol.com/­resourcesdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmldocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmldocs.microsoft.com/­en-us/­azure/­data-explorersitewhere1.sitewhere.io/­index.html
DeveloperExasolFairCom CorporationFairCom CorporationMicrosoftSiteWhere
Initial release20001979197920192010
Current releaseV12, November 2020V3, October 2020cloud service with continuous releases
License infoCommercial or Open Sourcecommercialcommercial infoRestricted, free version availablecommercial infoRestricted, free version availablecommercialOpen Source infoCommon Public Attribution License Version 1.0
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageANSI C, C++ANSI C, C++Java
Server operating systemsAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Android
Linux infoARM, x86
Raspbian
Windows
hostedLinux
OS X
Windows
Data schemeyesschema free, schema optional, schema required, partial schema,Flexible Schema (defined schema, partial schema, schema free)Fixed schema with schema-less datatypes (dynamic)predefined scheme
Typing infopredefined data types such as float or dateyesyes, ANSI SQL Types, JSON, typed binary structuresyes, ANSI Standard SQL Typesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes
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.nonoyesyesno
Secondary indexesyesyesyesall fields are automatically indexedno
SQL infoSupport of SQLyesyes, ANSI SQL with proprietary extensionsyes infoANSI SQL queriesKusto Query Language (KQL), SQL subsetno
APIs and other access methods.Net
JDBC
ODBC
WebSocket
ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP REST
Supported programming languagesJava
Lua
Python
R
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresuser defined functionsyes info.Net, JavaScript, C/C++yes info.Net, JavaScript, C/C++Yes, possible languages: KQL, Python, R
Triggersyesyesyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningFile partitioning infoCustomizable business rules for partitioningSharding infoImplicit feature of the cloud serviceSharding infobased on HBase
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 infoSynchronous and asynchronous realtime replication based on transaction logsyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoHadoop integrationnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate Consistency
Tunable Consistency
Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesyesyes infowhen using SQLnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDtunable from ACID to Eventually ConsistentACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoacross SQL and NoSQLyesyes
Durability infoSupport for making data persistentyesYes, 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.yesyesyesnono
User concepts infoAccess controlAccess rights for users, groups and roles according to SQL-standardFine grained access rights according to SQL-standard with additional protections for filesFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Azure Active Directory AuthenticationUsers with fine-grained authorization concept

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More resources
EXASOLFaircom DB infoformerly c-treeACEFaircom EDGE infoformerly c-treeEDGEMicrosoft Azure Data ExplorerSiteWhere
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