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DBMS > Heroic vs. IRONdb vs. Microsoft Azure Data Explorer vs. Yaacomo

System Properties Comparison Heroic vs. IRONdb vs. Microsoft Azure Data Explorer vs. Yaacomo

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Editorial information provided by DB-Engines
NameHeroic  Xexclude from comparisonIRONdb  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonYaacomo  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityFully managed big data interactive analytics platformOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelTime Series DBMSTime Series DBMSRelational DBMS infocolumn orientedRelational 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
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websitegithub.com/­spotify/­heroicwww.circonus.com/solutions/time-series-database/azure.microsoft.com/­services/­data-exploreryaacomo.com
Technical documentationspotify.github.io/­heroicdocs.circonus.com/irondb/category/getting-starteddocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperSpotifyCirconus LLC.MicrosoftQ2WEB GmbH
Initial release2014201720192009
Current releaseV0.10.20, January 2018cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC and C++
Server operating systemsLinuxhostedAndroid
Linux
Windows
Data schemeschema-freeschema-freeFixed schema with schema-less datatypes (dynamic)yes
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-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.nonoyesno
Secondary indexesyes infovia Elasticsearchnoall fields are automatically indexedyes
SQL infoSupport of SQLnoSQL-like query language (Circonus Analytics Query Language: CAQL)Kusto Query Language (KQL), SQL subsetyes
APIs and other access methodsHQL (Heroic Query Language, a JSON-based language)
HTTP API
HTTP APIMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
Supported programming languages.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
Server-side scripts infoStored proceduresnoyes, in LuaYes, possible languages: KQL, Python, R
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodeSharding infoImplicit feature of the cloud servicehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesconfigurable replication factor, datacenter awareyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate consistency per node, eventual consistency across nodesEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes
User concepts infoAccess controlnoAzure Active Directory Authenticationfine grained access rights according to SQL-standard

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More resources
HeroicIRONdbMicrosoft Azure Data ExplorerYaacomo
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