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DBMS > Amazon DocumentDB vs. Manticore Search vs. Microsoft Azure Data Explorer vs. Transwarp Hippo

System Properties Comparison Amazon DocumentDB vs. Manticore Search vs. Microsoft Azure Data Explorer vs. Transwarp Hippo

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonManticore Search  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTranswarp Hippo  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceMulti-storage database for search, including full-text search.Fully managed big data interactive analytics platformCloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets
Primary database modelDocument storeSearch engineRelational DBMS infocolumn orientedVector DBMS
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
Score1.91
Rank#131  Overall
#24  Document stores
Score0.29
Rank#302  Overall
#21  Search engines
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.05
Rank#386  Overall
#15  Vector DBMS
Websiteaws.amazon.com/­documentdbmanticoresearch.comazure.microsoft.com/­services/­data-explorerwww.transwarp.cn/­en/­subproduct/­hippo
Technical documentationaws.amazon.com/­documentdb/­resourcesmanual.manticoresearch.comdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperManticore SoftwareMicrosoft
Initial release2019201720192023
Current release6.0, February 2023cloud service with continuous releases1.0, May 2023
License infoCommercial or Open SourcecommercialOpen Source infoGPL version 2commercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++
Server operating systemshostedFreeBSD
Linux
macOS
Windows
hostedLinux
macOS
Data schemeschema-freeFixed schemaFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesInt, 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-typesVector, Numeric and String
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.noCan index from XMLyesno
Secondary indexesyesyes infofull-text index on all search fieldsall fields are automatically indexedno
SQL infoSupport of SQLnoSQL-like query languageKusto Query Language (KQL), SQL subsetno
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C++
Java
Python
Server-side scripts infoStored proceduresnouser defined functionsYes, possible languages: KQL, Python, Rno
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
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 serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasSynchronous 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 methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)noSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsyes infoisolated transactions for atomic changes and binary logging for safe writesnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoThe original contents of fields are not stored in the Manticore index.yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlAccess rights for users and rolesnoAzure Active Directory AuthenticationRole based access control and fine grained access rights

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More resources
Amazon DocumentDBManticore SearchMicrosoft Azure Data ExplorerTranswarp Hippo
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