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DBMS > Amazon DocumentDB vs. Microsoft Azure Data Explorer vs. Oracle Coherence vs. Sphinx

System Properties Comparison Amazon DocumentDB vs. Microsoft Azure Data Explorer vs. Oracle Coherence vs. Sphinx

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOracle Coherence  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceFully managed big data interactive analytics platformOracles in-memory data grid solutionOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeRelational DBMS infocolumn orientedKey-value storeSearch engine
Secondary database modelsDocument 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#132  Overall
#24  Document stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score1.92
Rank#130  Overall
#22  Key-value stores
Score5.98
Rank#56  Overall
#5  Search engines
Websiteaws.amazon.com/­documentdbazure.microsoft.com/­services/­data-explorerwww.oracle.com/­java/­coherencesphinxsearch.com
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.oracle.com/­en/­middleware/­standalone/­coherencesphinxsearch.com/­docs
DeveloperMicrosoftOracleSphinx Technologies Inc.
Initial release2019201920072001
Current releasecloud service with continuous releases14.1, August 20233.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++
Server operating systemshostedhostedAll OS with a Java VMFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeFixed schema with schema-less datatypes (dynamic)schema-freeyes
Typing infopredefined data types such as float or dateyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesno
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.noyesno
Secondary indexesyesall fields are automatically indexednoyes infofull-text index on all search fields
SQL infoSupport of SQLnoKusto Query Language (KQL), SQL subsetnoSQL-like query language (SphinxQL)
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JCache
JPA
RESTful HTTP API
Proprietary protocol
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C++
Java
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnoYes, possible languages: KQL, Python, Rnono
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoLive Eventsno
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoImplicit feature of the cloud serviceShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes, with selectable consistency levelnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)Spark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual 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 operationsnoconfigurableno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infooptionallyyes infoThe original contents of fields are not stored in the Sphinx index.
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 rolesAzure Active Directory Authenticationauthentification to access the cache via certificates or http basic authenticationno

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More resources
Amazon DocumentDBMicrosoft Azure Data ExplorerOracle CoherenceSphinx
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