DBMS > GeoMesa vs. Google BigQuery vs. Oracle Coherence

System Properties Comparison GeoMesa vs. Google BigQuery vs. Oracle Coherence

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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.

Large scale data warehouse service with append-only tables

Oracles in-memory data grid solution

Primary database model

Spatial DBMS

Relational DBMS

Key-value store

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

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

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

Website

www.geomesa.org

cloud.google.com/bigquery

www.oracle.com/java/coherence

Technical documentation

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

cloud.google.com/bigquery/docs

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

Developer

CCRi and others

Google

Oracle

Initial release

2014

2010

2007

Current release

4.0.5, February 2024

14.1, August 2023

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Scala

Java

Server operating systems

hosted

All OS with a Java VM

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

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

yes

APIs and other access methods

RESTful HTTP/JSON API

JCache
JPA
RESTful HTTP API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C++
Java

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Triggers

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

yes, with selectable consistency level

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

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Since BigQuery is designed for querying data

configurable

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

In-memory capabilities

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

depending on storage layer

yes

User concepts

Access control

yes

depending on the DBMS used for storage

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

authentification to access the cache via certificates or http basic authentication

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