DBMS > GeoMesa vs. GridGain vs. ObjectBox vs. Oracle NoSQL

System Properties Comparison GeoMesa vs. GridGain vs. ObjectBox vs. Oracle NoSQL

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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.

GridGain is an in-memory computing platform, built on Apache Ignite

Extremely fast embedded database for small devices, IoT and Mobile

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Primary database model

Spatial DBMS

Key-value store
Relational DBMS

Object oriented DBMS

Document store
Key-value store
Relational DBMS

Secondary database models

Time Series DBMS

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

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	1.20
Rank	#170	Overall
	#5	Object oriented DBMS

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Website

www.geomesa.org

www.gridgain.com

objectbox.io

www.oracle.com/database/nosql/technologies/nosql

Technical documentation

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

www.gridgain.com/docs/index.html

docs.objectbox.io

docs.oracle.com/en/database/other-databases/nosql-database/index.html

Developer

CCRi and others

GridGain Systems, Inc.

ObjectBox Limited

Oracle

Initial release

2014

2007

2017

2011

Current release

4.0.5, February 2024

GridGain 8.5.1

23.3, December 2023

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Open Source

Apache License 2.0

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Scala

Java, C++, .Net

C and C++

Java

Server operating systems

Linux
OS X
Solaris
Windows

Android
iOS
Linux
macOS
Windows

Linux
Solaris SPARC/x86

Data scheme

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

Typing

predefined data types such as float or date

yes

optional

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.

yes

Secondary indexes

yes

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

SQL-like DML and DDL statements

APIs and other access methods

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

Proprietary native API

RESTful HTTP API

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

C
C#
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

Triggers

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

yes (replicated cache)

online/offline synchronization between client and server

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

yes (compute grid and hadoop accelerator)

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

depending on storage layer

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

configurable

ACID within a storage node (=shard)

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

off heap cache

User concepts

Access control

yes

depending on the DBMS used for storage

Security Hooks for custom implementations

yes

Access rights for users and roles

More information provided by the system vendor

News

Edge AI: The era of on-device AI
23 April 2024

In-Memory Database Use Cases
15 February 2024

Data Viewer for Objects – announcing ObjectBox Admin
14 November 2023

Vector Databases for Edge AI
9 August 2023

Vector Database Release for Flutter / Dart + Python
13 June 2023

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