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DBMS > GeoSpock vs. Microsoft Azure Data Explorer vs. MongoDB vs. PostgreSQL

System Properties Comparison GeoSpock vs. Microsoft Azure Data Explorer vs. MongoDB vs. PostgreSQL

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Editorial information provided by DB-Engines
NameGeoSpock  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonMongoDB  Xexclude from comparisonPostgreSQL  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
DescriptionSpatial and temporal data processing engine for extreme data scaleFully managed big data interactive analytics platformOne of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructureWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL
Primary database modelRelational DBMSRelational DBMS infocolumn orientedDocument storeRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.
Secondary database modelsTime Series DBMSDocument 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
Spatial DBMS
Search engine infointegrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS infoTime Series Collections introduced in Release 5.0
Vector DBMS infocurrently available in the MongoDB Atlas cloud service only
Document store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score421.65
Rank#5  Overall
#1  Document stores
Score645.54
Rank#4  Overall
#4  Relational DBMS
Websitegeospock.comazure.microsoft.com/­services/­data-explorerwww.mongodb.comwww.postgresql.org
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorerwww.mongodb.com/­docs/­manualwww.postgresql.org/­docs
DeveloperGeoSpockMicrosoftMongoDB, IncPostgreSQL Global Development Group infowww.postgresql.org/­developer
Initial release201920091989 info1989: Postgres, 1996: PostgreSQL
Current release2.0, September 2019cloud service with continuous releases6.0.7, June 202316.2, February 2024
License infoCommercial or Open SourcecommercialcommercialOpen Source infoMongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.Open Source infoBSD
Cloud-based only infoOnly available as a cloud serviceyesyesno infoMongoDB available as DBaaS (MongoDB Atlas)no
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
MongoDB Atlas: Global multi-cloud database with unmatched data distribution and mobility across AWS, Azure, and Google Cloud, built-in automation for resource and workload optimization, and so much more.Aiven for PostgreSQL: Fully managed PostgreSQL for developers with 70+ extensions and flexible orchestration tools.
Implementation languageJava, JavascriptC++C
Server operating systemshostedhostedLinux
OS X
Solaris
Windows
FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Data schemeyesFixed schema with schema-less datatypes (dynamic)schema-free infoAlthough schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.yes
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-typesyes infostring, integer, double, decimal, boolean, date, object_id, geospatialyes
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.noyesyes infospecific XML-type available, but no XML query functionality.
Secondary indexestemporal, categoricalall fields are automatically indexedyesyes
SQL infoSupport of SQLANSI SQL for query only (using Presto)Kusto Query Language (KQL), SQL subsetRead-only SQL queries via the MongoDB Atlas SQL Interfaceyes infostandard with numerous extensions
APIs and other access methodsJDBCMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
GraphQL
HTTP REST
Prisma
proprietary protocol using JSON
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Actionscript infounofficial driver
C
C#
C++
Clojure infounofficial driver
ColdFusion infounofficial driver
D infounofficial driver
Dart infounofficial driver
Delphi infounofficial driver
Erlang
Go
Groovy infounofficial driver
Haskell
Java
JavaScript
Kotlin
Lisp infounofficial driver
Lua infounofficial driver
MatLab infounofficial driver
Perl
PHP
PowerShell infounofficial driver
Prolog infounofficial driver
Python
R infounofficial driver
Ruby
Rust
Scala
Smalltalk infounofficial driver
Swift
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresnoYes, possible languages: KQL, Python, RJavaScriptuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoin MongoDB Atlas onlyyes
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingSharding infoImplicit feature of the cloud serviceSharding infoPartitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.partitioning by range, list and (since PostgreSQL 11) by hash
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication
Source-replica replication infoother methods possible by using 3rd party extensions
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency infocan be individually decided for each read operation
Immediate Consistency infodefault behaviour
Immediate Consistency
Foreign keys infoReferential integritynonono infotypically not used, however similar functionality with DBRef possibleyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoMulti-document ACID Transactions with snapshot isolationACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infooptional, enabled by defaultyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes infoIn-memory storage engine introduced with MongoDB version 3.2no
User concepts infoAccess controlAccess rights for users can be defined per tableAzure Active Directory AuthenticationAccess rights for users and rolesfine grained access rights according to SQL-standard
More information provided by the system vendor
GeoSpockMicrosoft Azure Data ExplorerMongoDBPostgreSQL
Specific characteristicsMongoDB provides an integrated suite of cloud database and data services to accelerate...
» more
Competitive advantagesBuilt around the flexible document data model and unified API, MongoDB is a developer...
» more
Typical application scenariosAI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
» more
Key customersADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
» more
Market metricsHundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
» more
Licensing and pricing modelsMongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
» more

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More resources
GeoSpockMicrosoft Azure Data ExplorerMongoDBPostgreSQL
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