DBMS > GeoSpock vs. Microsoft Azure Synapse Analytics vs. MongoDB

System Properties Comparison GeoSpock vs. Microsoft Azure Synapse Analytics vs. MongoDB

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Editorial information provided by DB-Engines

Name

Description

Spatial and temporal data processing engine for extreme data scale

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure

Primary database model

Relational DBMS

Document store

Secondary database models

Time Series DBMS

Spatial DBMS
Search engine

integrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS

Time Series Collections introduced in Release 5.0

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.42
Rank	#316	Overall
	#141	Relational DBMS

Score	23.28
Rank	#32	Overall
	#19	Relational DBMS

Score	436.61
Rank	#5	Overall
	#1	Document stores

Website

geospock.com

azure.microsoft.com/services/synapse-analytics

www.mongodb.com

Technical documentation

docs.geospock.com/Content/Home.htm

docs.microsoft.com/azure/synapse-analytics

docs.mongodb.com/manual

Developer

GeoSpock

Microsoft

MongoDB, Inc

Initial release

2016

2009

Current release

2.0, September 2019

6.0.5, March 2023

License

Commercial or Open Source

commercial

Open Source

MongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.

Cloud-based only

Only available as a cloud service

yes

MongoDB available as DBaaS (MongoDB Atlas)

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

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Implementation language

Java, Javascript

C++

Server operating systems

hosted

Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

Although 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.

Typing

predefined data types such as float or date

yes

string, integer, double, decimal, boolean, date, object_id, geospatial

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

temporal, categorical

yes

SQL

Support of SQL

ANSI SQL for query only (using Presto)

yes

Read-only SQL queries via the MongoDB Connector for BI

APIs and other access methods

JDBC

ADO.NET
JDBC
ODBC

proprietary protocol using JSON

Supported programming languages

C#
Java
PHP

Actionscript

unofficial driver
C
C#
C++
Clojure

unofficial driver
ColdFusion

unofficial driver
D

unofficial driver
Dart

unofficial driver
Delphi

unofficial driver
Erlang
Go
Groovy

unofficial driver
Haskell
Java
JavaScript
Lisp

unofficial driver
Lua

unofficial driver
MatLab

unofficial driver
Perl
PHP
PowerShell

unofficial driver
Prolog

unofficial driver
Python
R

unofficial driver
Ruby
Rust
Scala
Smalltalk

unofficial driver
Swift

Server-side scripts

Stored procedures

Transact SQL

JavaScript

Triggers

yes

in MongoDB Atlas only

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding, horizontal partitioning

Sharding

Partitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Foreign keys

Referential integrity

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

typically not used, however similar functionality with DBRef possible

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Multi-document ACID Transactions with snapshot isolation

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional, enabled by default

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

In-memory storage engine introduced with MongoDB version 3.2

User concepts

Access control

Access rights for users can be defined per table

yes

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

MongoDB provides an integrated suite of cloud database and data services to accelerate...
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Competitive advantages

Built around the flexible document data model and unified API, MongoDB is a developer...
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Typical application scenarios

Internet of Things and Time Series (Bosch, GE Healthcare, Jaguar Land Rover) Mobile...
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Key customers

ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
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Market metrics

365+ million downloads, over 150,000+ Atlas clusters provisioned every month handling...
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Licensing and pricing models

MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
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