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DBMS > Heroic vs. Microsoft Azure AI Search vs. OpenQM vs. Vertica

System Properties Comparison Heroic vs. Microsoft Azure AI Search vs. OpenQM vs. Vertica

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Editorial information provided by DB-Engines
NameHeroic  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonOpenQM infoalso called QM  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchSearch-as-a-service for web and mobile app developmentQpenQM is a high-performance, self-tuning, multi-value DBMSCloud 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.
Primary database modelTime Series DBMSSearch engineMultivalue DBMSRelational DBMS infoColumn oriented
Secondary database modelsVector DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score5.59
Rank#63  Overall
#7  Search engines
Score0.27
Rank#298  Overall
#10  Multivalue DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitegithub.com/­spotify/­heroicazure.microsoft.com/­en-us/­services/­searchwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-open-qmwww.vertica.com
Technical documentationspotify.github.io/­heroiclearn.microsoft.com/­en-us/­azure/­searchvertica.com/­documentation
DeveloperSpotifyMicrosoftRocket Software, originally Martin PhillipsOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2014201519932005
Current releaseV13.4-1212.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoGPLv2, extended commercial license availablecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenoyesnono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++
Server operating systemshostedAIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows
Linux
Data schemeschema-freeyesyes infowith some exceptionsYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateyesyesyes
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 ElasticsearchyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnononoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsHQL (Heroic Query Language, a JSON-based language)
HTTP API
RESTful HTTP APIADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC#
Java
JavaScript
Python
.Net
Basic
C
Java
Objective C
PHP
Python
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnonoyesyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnonoyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceyeshorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoImplicit feature of the cloud serviceyesMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID
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.nonono
User concepts infoAccess controlyes infousing Azure authenticationAccess rights can be defined down to the item levelfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
HeroicMicrosoft Azure AI SearchOpenQM infoalso called QMVertica infoOpenText™ Vertica™
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 AI SearchOpenQM infoalso called QMVertica infoOpenText™ Vertica™
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