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DBMS > Heroic vs. Microsoft Azure Data Explorer vs. mSQL vs. Vertica vs. Yaacomo

System Properties Comparison Heroic vs. Microsoft Azure Data Explorer vs. mSQL vs. Vertica vs. Yaacomo

Editorial information provided by DB-Engines
NameHeroic  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonmSQL infoMini SQL  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparisonYaacomo  Xexclude from comparison
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 ElasticSearchFully managed big data interactive analytics platformmSQL (Mini SQL) is a simple and lightweight RDBMSCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelTime Series DBMSRelational DBMS infocolumn orientedRelational 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
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score1.27
Rank#169  Overall
#76  Relational DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitegithub.com/­spotify/­heroicazure.microsoft.com/­services/­data-explorerhughestech.com.au/­products/­msqlwww.vertica.comyaacomo.com
Technical documentationspotify.github.io/­heroicdocs.microsoft.com/­en-us/­azure/­data-explorervertica.com/­documentation
DeveloperSpotifyMicrosoftHughes TechnologiesOpenText infopreviously Micro Focus and Hewlett PackardQ2WEB GmbH
Initial release20142019199420052009
Current releasecloud service with continuous releases4.4, October 202112.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercial infofree licenses can be providedcommercial infoLimited community edition freecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containersno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCC++
Server operating systemshostedAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
LinuxAndroid
Linux
Windows
Data schemeschema-freeFixed schema with schema-less datatypes (dynamic)yesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.yes
Typing infopredefined data types such as float or dateyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyesyes
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.noyesnonono
Secondary indexesyes infovia Elasticsearchall fields are automatically indexedyesNo Indexes Required. Different internal optimization strategy, but same functionality included.yes
SQL infoSupport of SQLnoKusto Query Language (KQL), SQL subsetA subset of ANSI SQL is implemented infono subqueries, aggregate functions, views, foreign keys, triggersFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.yes
APIs and other access methodsHQL (Heroic Query Language, a JSON-based language)
HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
JDBC
ODBC
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C++
Delphi
Java
Perl
PHP
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnoYes, possible languages: KQL, Python, Rnoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes, called Custom Alertsyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicenonehorizontal partitioning, hierarchical partitioninghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.noneMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono infoBi-directional Spark integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency
noneImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesnoyesyes
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.nonononoyes
User concepts infoAccess controlAzure Active Directory Authenticationnofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hashfine grained access rights according to SQL-standard
More information provided by the system vendor
HeroicMicrosoft Azure Data ExplorermSQL infoMini SQLVertica infoOpenText™ Vertica™Yaacomo
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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More resources
HeroicMicrosoft Azure Data ExplorermSQL infoMini SQLVertica infoOpenText™ Vertica™Yaacomo
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