DBMS > GeoMesa vs. MongoDB vs. Oracle Coherence vs. Warp 10

System Properties Comparison GeoMesa vs. MongoDB vs. Oracle Coherence vs. Warp 10

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Editorial information provided by DB-Engines

Name

Description

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

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

Oracles in-memory data grid solution

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Secondary database models

Spatial DBMS
Search engine

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

Time Series Collections introduced in Release 5.0
Vector DBMS

currently available in the MongoDB Atlas cloud service only

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

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	421.65
Rank	#5	Overall
	#1	Document stores

Score	1.92
Rank	#130	Overall
	#22	Key-value stores

Score	0.07
Rank	#349	Overall
	#32	Time Series DBMS

Website

www.geomesa.org

www.mongodb.com

www.oracle.com/java/coherence

www.warp10.io

Technical documentation

www.geomesa.org/documentation/stable/user/index.html

www.mongodb.com/docs/manual

docs.oracle.com/en/middleware/standalone/coherence

www.warp10.io/content/02_Getting_started

Developer

CCRi and others

MongoDB, Inc

Oracle

SenX

Initial release

2014

2009

2007

2015

Current release

5.0.0, May 2024

6.0.7, June 2023

14.1, August 2023

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

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

commercial

Open Source

Apache License 2.0

Cloud-based only

Only available as a cloud service

MongoDB available as DBaaS (MongoDB Atlas)

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Scala

C++

Java

Server operating systems

Linux
OS X
Solaris
Windows

All OS with a Java VM

Linux
OS X
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.

schema-free

Typing

predefined data types such as float or date

yes

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

yes

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

yes

SQL

Support of SQL

Read-only SQL queries via the MongoDB Atlas SQL Interface

APIs and other access methods

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

JCache
JPA
RESTful HTTP API

HTTP API
Jupyter
WebSocket

Supported programming languages

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
Kotlin
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

.Net
C++
Java

Server-side scripts

Stored procedures

JavaScript

yes

WarpScript

Triggers

yes

in MongoDB Atlas only

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

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.

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

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

yes, with selectable consistency level

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

depending on storage layer

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Eventual Consistency
Immediate Consistency

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

Transaction concepts

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

Multi-document ACID Transactions with snapshot isolation

configurable

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional, enabled by default

yes

optionally

yes

In-memory capabilities

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

depending on storage layer

yes

In-memory storage engine introduced with MongoDB version 3.2

yes

User concepts

Access control

yes

depending on the DBMS used for storage

Access rights for users and roles

authentification to access the cache via certificates or http basic authentication

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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

AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
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Key customers

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

Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
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Licensing and pricing models

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