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DBMS > Faircom EDGE vs. Hawkular Metrics vs. InterSystems Caché vs. Microsoft Azure Data Explorer vs. TimescaleDB

System Properties Comparison Faircom EDGE vs. Hawkular Metrics vs. InterSystems Caché vs. Microsoft Azure Data Explorer vs. TimescaleDB

Editorial information provided by DB-Engines
NameFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTimescaleDB  Xexclude from comparison
Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.
DescriptionFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.A multi-model DBMS and application serverFully managed big data interactive analytics platformA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelKey-value store
Relational DBMS
Time Series DBMSKey-value store
Object oriented DBMS
Relational DBMS
Relational DBMS infocolumn orientedTime Series DBMS
Secondary database modelsDocument storeDocument 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
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.02
Rank#368  Overall
#54  Key-value stores
#156  Relational DBMS
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitewww.faircom.com/­products/­faircom-edgewww.hawkular.orgwww.intersystems.com/­products/­cacheazure.microsoft.com/­services/­data-explorerwww.timescale.com
Technical documentationdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlwww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.intersystems.comdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.timescale.com
DeveloperFairCom CorporationCommunity supported by Red HatInterSystemsMicrosoftTimescale
Initial release19792014199720192017
Current releaseV3, October 20202018.1.4, May 2020cloud service with continuous releases2.13.0, November 2023
License infoCommercial or Open Sourcecommercial infoRestricted, free version availableOpen Source infoApache 2.0commercialcommercialOpen Source infoApache 2.0
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++JavaC
Server operating systemsAndroid
Linux infoARM, x86
Raspbian
Windows
Linux
OS X
Windows
AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
hostedLinux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freedepending on used data modelFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyes, ANSI Standard SQL Typesyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.yesnoyesyesyes
Secondary indexesyesnoyesall fields are automatically indexedyes
SQL infoSupport of SQLyes infoANSI SQL queriesnoyesKusto Query Language (KQL), SQL subsetyes infofull PostgreSQL SQL syntax
APIs and other access methodsADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
HTTP REST.NET Client API
JDBC
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C#
C++
Java
JavaScript
PHP
Python
VB.Net
Go
Java
Python
Ruby
C#
C++
Java
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++noyesYes, possible languages: KQL, Python, Ruser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyesyes infovia Hawkular Alertingyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesFile partitioning infoCustomizable business rules for partitioningSharding infobased on CassandranoneSharding infoImplicit feature of the cloud serviceyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoSynchronous and asynchronous realtime replication based on transaction logsselectable replication factor infobased on CassandraSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Tunable Consistency
Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyes infowhen using SQLnoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayes infoacross SQL and NoSQLyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesnono
User concepts infoAccess controlFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.noAccess rights for users, groups and rolesAzure Active Directory Authenticationfine grained access rights according to SQL-standard

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More resources
Faircom EDGE infoformerly c-treeEDGEHawkular MetricsInterSystems CachéMicrosoft Azure Data ExplorerTimescaleDB
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