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DBMS > Hawkular Metrics vs. IRONdb vs. Microsoft Azure Data Explorer vs. TimescaleDB vs. Yanza

System Properties Comparison Hawkular Metrics vs. IRONdb vs. Microsoft Azure Data Explorer vs. TimescaleDB vs. Yanza

Editorial information provided by DB-Engines
NameHawkular Metrics  Xexclude from comparisonIRONdb  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTimescaleDB  Xexclude from comparisonYanza  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityFully managed big data interactive analytics platformA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLTime Series DBMS for IoT Applications
Primary database modelTime Series DBMSTime Series DBMSRelational DBMS infocolumn orientedTime Series DBMSTime 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
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
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
Websitewww.hawkular.orgwww.circonus.com/solutions/time-series-database/azure.microsoft.com/­services/­data-explorerwww.timescale.comyanza.com
Technical documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.circonus.com/irondb/category/getting-starteddocs.microsoft.com/­en-us/­azure/­data-explorerdocs.timescale.com
DeveloperCommunity supported by Red HatCirconus LLC.MicrosoftTimescaleYanza
Initial release20142017201920172015
Current releaseV0.10.20, January 2018cloud service with continuous releases2.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialOpen Source infoApache 2.0commercial infofree version available
Cloud-based only infoOnly available as a cloud servicenonoyesnono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC and C++C
Server operating systemsLinux
OS X
Windows
LinuxhostedLinux
OS X
Windows
Windows
Data schemeschema-freeschema-freeFixed schema with schema-less datatypes (dynamic)yesschema-free
Typing infopredefined data types such as float or dateyesyes infotext, numeric, histogramsyes 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 typesno
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 indexesnonoall fields are automatically indexedyesno
SQL infoSupport of SQLnoSQL-like query language (Circonus Analytics Query Language: CAQL)Kusto Query Language (KQL), SQL subsetyes infofull PostgreSQL SQL syntaxno
APIs and other access methodsHTTP RESTHTTP APIMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HTTP API
Supported programming languagesGo
Java
Python
Ruby
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
any language that supports HTTP calls
Server-side scripts infoStored proceduresnoyes, in LuaYes, 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
Triggersyes infovia Hawkular Alertingnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraAutomatic, metric affinity per nodeSharding infoImplicit feature of the cloud serviceyes, across time and space (hash partitioning) attributesnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on Cassandraconfigurable replication factor, datacenter awareyes 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 systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate consistency per node, eventual consistency across nodesEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.nononono
User concepts infoAccess controlnonoAzure Active Directory Authenticationfine grained access rights according to SQL-standardno

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More resources
Hawkular MetricsIRONdbMicrosoft Azure Data ExplorerTimescaleDBYanza
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