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DBMS > Amazon DynamoDB vs. Fauna vs. Manticore Search vs. Microsoft Azure Data Explorer vs. STSdb

System Properties Comparison Amazon DynamoDB vs. Fauna vs. Manticore Search vs. Microsoft Azure Data Explorer vs. STSdb

Editorial information provided by DB-Engines
NameAmazon DynamoDB  Xexclude from comparisonFauna infopreviously named FaunaDB  Xexclude from comparisonManticore Search  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSTSdb  Xexclude from comparison
DescriptionHosted, scalable database service by Amazon with the data stored in Amazons cloudFauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.Multi-storage database for search, including full-text search.Fully managed big data interactive analytics platformKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelDocument store
Key-value store
Document store
Graph DBMS
Relational DBMS
Time Series DBMS
Search engineRelational DBMS infocolumn orientedKey-value store
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
Score74.07
Rank#17  Overall
#3  Document stores
#2  Key-value stores
Score1.52
Rank#153  Overall
#26  Document stores
#14  Graph DBMS
#71  Relational DBMS
#13  Time Series DBMS
Score0.22
Rank#312  Overall
#21  Search engines
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.04
Rank#360  Overall
#52  Key-value stores
Websiteaws.amazon.com/­dynamodbfauna.commanticoresearch.comazure.microsoft.com/­services/­data-explorergithub.com/­STSSoft/­STSdb4
Technical documentationdocs.aws.amazon.com/­dynamodbdocs.fauna.commanual.manticoresearch.comdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperAmazonFauna, Inc.Manticore SoftwareMicrosoftSTS Soft SC
Initial release20122014201720192011
Current release6.0, February 2023cloud service with continuous releases4.0.8, September 2015
License infoCommercial or Open Sourcecommercial infofree tier for a limited amount of database operationscommercialOpen Source infoGPL version 2commercialOpen Source infoGPLv2, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageScalaC++C#
Server operating systemshostedhostedFreeBSD
Linux
macOS
Windows
hostedWindows
Data schemeschema-freeschema-freeFixed schemaFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesnoInt, 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-typesyes infoprimitive types and user defined types (classes)
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 XMLyes
Secondary indexesyesyesyes infofull-text index on all search fieldsall fields are automatically indexedno
SQL infoSupport of SQLnonoSQL-like query languageKusto Query Language (KQL), SQL subsetno
APIs and other access methodsRESTful HTTP APIRESTful HTTP APIBinary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
.NET Client API
Supported programming languages.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby
C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C#
Java
Server-side scripts infoStored proceduresnouser defined functionsuser defined functionsYes, possible languages: KQL, Python, Rno
Triggersyes infoby integration with AWS Lambdanonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infoconsistent hashingSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replicationSynchronous replication based on Galera libraryyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Immediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoACID across one or more tables within a single AWS account and regionACIDyes infoisolated transactions for atomic changes and binary logging for safe writesnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes 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.nono
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Identity management, authentication, and access controlnoAzure Active Directory Authenticationno

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More resources
Amazon DynamoDBFauna infopreviously named FaunaDBManticore SearchMicrosoft Azure Data ExplorerSTSdb
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