DBMS > atoti vs. GeoMesa vs. OrigoDB

System Properties Comparison atoti vs. GeoMesa vs. OrigoDB

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Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

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

A fully ACID in-memory object graph database

Primary database model

Object oriented DBMS

Spatial DBMS

Document store
Object oriented DBMS

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

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Website

atoti.io

www.geomesa.org

origodb.com

Technical documentation

docs.atoti.io

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

origodb.com/docs

Developer

ActiveViam

CCRi and others

Robert Friberg et al

Initial release

2014

2009

under the name LiveDB

Current release

4.0.5, February 2024

License

Commercial or Open Source

commercial

free versions available

Open Source

Apache License 2.0

Open Source

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Scala

Server operating systems

Linux
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

Multidimensional Expressions (MDX)

APIs and other access methods

.NET Client API
HTTP API
LINQ

Supported programming languages

.Net

Server-side scripts

Stored procedures

Python

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

depending on storage layer

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

Source-replica replication

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

Foreign keys

Referential integrity

depending on model

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

Write ahead log

In-memory capabilities

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

yes

depending on storage layer

yes

User concepts

Access control

yes

depending on the DBMS used for storage

Role based authorization

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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