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DBMS > Manticore Search vs. Microsoft Azure Data Explorer

System Properties Comparison Manticore Search vs. Microsoft Azure Data Explorer

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Our visitors often compare Manticore Search and Microsoft Azure Data Explorer with Elasticsearch, ClickHouse and PostgreSQL.

Editorial information provided by DB-Engines
NameManticore Search  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionMulti-storage database for search, including full-text search.Fully managed big data interactive analytics platform
Primary database modelSearch engineRelational DBMS infocolumn oriented
Secondary database modelsTime Series DBMS infousing the Manticore Columnar LibraryDocument 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
Score0.22
Rank#312  Overall
#21  Search engines
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websitemanticoresearch.comazure.microsoft.com/­services/­data-explorer
Technical documentationmanual.manticoresearch.comdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperManticore SoftwareMicrosoft
Initial release20172019
Current release6.0, February 2023cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoGPL version 2commercial
Cloud-based only infoOnly available as a cloud servicenoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++
Server operating systemsFreeBSD
Linux
macOS
Windows
hosted
Data schemeFixed schemaFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Booleanyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types
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.Can index from XMLyes
Secondary indexesyes infofull-text index on all search fieldsall fields are automatically indexed
SQL infoSupport of SQLSQL-like query languageKusto Query Language (KQL), SQL subset
APIs and other access methodsBinary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesElixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresuser defined functionsYes, possible languages: KQL, Python, R
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesSynchronous replication based on Galera libraryyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infoisolated transactions for atomic changes and binary logging for safe writesno
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyes infoThe original contents of fields are not stored in the Manticore index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlnoAzure Active Directory Authentication

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More resources
Manticore SearchMicrosoft Azure Data Explorer
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