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DBMS > EJDB vs. Manticore Search vs. Microsoft Azure Data Explorer

System Properties Comparison EJDB vs. Manticore Search vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines
NameEJDB  Xexclude from comparisonManticore Search  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionEmbeddable document-store database library with JSON representation of queries (in MongoDB style)Multi-storage database for search, including full-text search.Fully managed big data interactive analytics platform
Primary database modelDocument storeSearch 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
Score0.30
Rank#294  Overall
#44  Document stores
Score0.23
Rank#317  Overall
#21  Search engines
Score5.16
Rank#69  Overall
#37  Relational DBMS
Websitegithub.com/­Softmotions/­ejdbmanticoresearch.comazure.microsoft.com/­services/­data-explorer
Technical documentationgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mdmanual.manticoresearch.comdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperSoftmotionsManticore SoftwareMicrosoft
Initial release201220172019
Current release6.0, February 2023cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoGPLv2Open Source infoGPL version 2commercial
Cloud-based only infoOnly available as a cloud servicenonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCC++
Server operating systemsserver-lessFreeBSD
Linux
macOS
Windows
hosted
Data schemeschema-freeFixed schemaFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyes infostring, integer, double, bool, date, object_idInt, 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 indexesnoyes infofull-text index on all search fieldsall fields are automatically indexed
SQL infoSupport of SQLnoSQL-like query languageKusto Query Language (KQL), SQL subset
APIs and other access methodsin-process shared libraryBinary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesActionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresnouser defined functionsYes, possible languages: KQL, Python, R
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesnoneSharding 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 nodesnoneSynchronous 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 methodsnonoSpark 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 integrityno infotypically not needed, however similar functionality with collection joins possiblenono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyes infoisolated transactions for atomic changes and binary logging for safe writesno
Concurrency infoSupport for concurrent manipulation of datayes infoRead/Write Lockingyesyes
Durability infoSupport for making data persistentyesyes 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 controlnonoAzure Active Directory Authentication

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More resources
EJDBManticore SearchMicrosoft Azure Data Explorer
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