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DBMS > Microsoft Azure AI Search vs. Prometheus vs. Sadas Engine vs. Vertica

System Properties Comparison Microsoft Azure AI Search vs. Prometheus vs. Sadas Engine vs. Vertica

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Editorial information provided by DB-Engines
NameMicrosoft Azure AI Search  Xexclude from comparisonPrometheus  Xexclude from comparisonSadas Engine  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionSearch-as-a-service for web and mobile app developmentOpen-source Time Series DBMS and monitoring systemSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsCloud 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 modelSearch engineTime Series DBMSRelational 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
Score5.59
Rank#63  Overall
#7  Search engines
Score8.42
Rank#47  Overall
#2  Time Series DBMS
Score0.00
Rank#383  Overall
#158  Relational DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websiteazure.microsoft.com/­en-us/­services/­searchprometheus.iowww.sadasengine.comwww.vertica.com
Technical documentationlearn.microsoft.com/­en-us/­azure/­searchprometheus.io/­docswww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationvertica.com/­documentation
DeveloperMicrosoftSADAS s.r.l.OpenText infopreviously Micro Focus and Hewlett Packard
Initial release2015201520062005
Current releaseV18.012.0.3, January 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercial infofree trial version availablecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud serviceyesnonono 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 languageGoC++C++
Server operating systemshostedLinux
Windows
AIX
Linux
Windows
Linux
Data schemeyesyesyesYes, 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 dateyesNumeric data onlyyesyes
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.nono infoImport of XML data possiblenono
Secondary indexesyesnoyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnonoyesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsRESTful HTTP APIRESTful HTTP/JSON APIJDBC
ODBC
Proprietary protocol
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC#
Java
JavaScript
Python
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
.Net
C
C#
C++
Groovy
Java
PHP
Python
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnononoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnononoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceShardinghorizontal partitioninghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceyes infoby FederationnoneMulti-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 systemImmediate ConsistencynoneImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID
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.nonoyes infomanaged by 'Learn by Usage'no
User concepts infoAccess controlyes infousing Azure authenticationnoAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Microsoft Azure AI SearchPrometheusSadas EngineVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
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...
» more
Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
» more

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More resources
Microsoft Azure AI SearchPrometheusSadas EngineVertica infoOpenText™ Vertica™
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