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

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

Editorial information provided by DB-Engines
NameFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTimescaleDB  Xexclude from comparisonTinkerGraph  Xexclude from comparison
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.Fully managed big data interactive analytics platformA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLA lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API
Primary database modelKey-value store
Relational DBMS
Time Series DBMSRelational DBMS infocolumn orientedTime Series DBMSGraph 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
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.09
Rank#362  Overall
#53  Key-value stores
#155  Relational DBMS
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Score0.13
Rank#345  Overall
#35  Graph DBMS
Websitewww.faircom.com/­products/­faircom-edgewww.hawkular.orgazure.microsoft.com/­services/­data-explorerwww.timescale.comtinkerpop.apache.org/­docs/­current/­reference/­#tinkergraph-gremlin
Technical documentationdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlwww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.microsoft.com/­en-us/­azure/­data-explorerdocs.timescale.com
DeveloperFairCom CorporationCommunity supported by Red HatMicrosoftTimescale
Initial release19792014201920172009
Current releaseV3, October 2020cloud service with continuous releases2.15.0, May 2024
License infoCommercial or Open Sourcecommercial infoRestricted, free version availableOpen Source infoApache 2.0commercialOpen Source infoApache 2.0Open Source infoApache 2.0
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++JavaCJava
Server operating systemsAndroid
Linux infoARM, x86
Raspbian
Windows
Linux
OS X
Windows
hostedLinux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeFixed schema with schema-less datatypes (dynamic)yesschema-free
Typing infopredefined data types such as float or dateyes, ANSI Standard SQL Typesyesyes 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 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.yesnoyesyesno
Secondary indexesyesnoall fields are automatically indexedyesno
SQL infoSupport of SQLyes infoANSI SQL queriesnoKusto Query Language (KQL), SQL subsetyes infofull PostgreSQL SQL syntaxno
APIs and other access methodsADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
HTTP RESTMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
TinkerPop 3
Supported programming languagesC
C#
C++
Java
JavaScript
PHP
Python
VB.Net
Go
Java
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Groovy
Java
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++noYes, 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 shellno
Triggersyesyes infovia Hawkular Alertingyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesno
Partitioning methods infoMethods for storing different data on different nodesFile partitioning infoCustomizable business rules for partitioningSharding infobased on CassandraSharding infoImplicit feature of the cloud serviceyes, across time and space (hash partitioning) attributesnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoSynchronous and asynchronous realtime replication based on transaction logsselectable replication factor infobased on Cassandrayes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication with hot standby and reads on replicas infonone
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 systemImmediate Consistency
Tunable Consistency
Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual Consistency
Immediate Consistency
Immediate Consistencynone
Foreign keys infoReferential integrityyes infowhen using SQLnonoyesyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACIDno
Concurrency infoSupport for concurrent manipulation of datayes infoacross SQL and NoSQLyesyesyesno
Durability infoSupport for making data persistentyesyesyesyesoptional
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnononoyes
User concepts infoAccess controlFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.noAzure Active Directory Authenticationfine grained access rights according to SQL-standardno

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More resources
Faircom EDGE infoformerly c-treeEDGEHawkular MetricsMicrosoft Azure Data ExplorerTimescaleDBTinkerGraph
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