DBMS > atoti vs. chDB vs. GeoMesa

System Properties Comparison atoti vs. chDB vs. GeoMesa

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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.

An embedded SQL OLAP Engine powered by ClickHouse

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

Primary database model

Object oriented DBMS

Relational DBMS

Spatial DBMS

Secondary database models

Time Series DBMS

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

Score	0.61
Rank	#243	Overall
	#11	Object oriented DBMS

Score	0.07
Rank	#376	Overall
	#158	Relational DBMS

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Website

atoti.io

github.com/chdb-io/chdb

www.geomesa.org

Technical documentation

docs.atoti.io

doc.chdb.io

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

Developer

ActiveViam

CCRi and others

Initial release

2023

2014

Current release

5.0.0, May 2024

License

Commercial or Open Source

commercial

free versions available

Open Source

Apache Version 2.0

Open Source

Apache License 2.0

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

Java

Scala

Server operating systems

server-less

Data scheme

yes

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

Multidimensional Expressions (MDX)

Close to ANSI SQL (SQL/JSON + extensions)

Supported programming languages

Bun
C
C++
Go
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

Python

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

depending on storage layer

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

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

Transaction concepts

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

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

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.

yes

depending on storage layer

User concepts

Access control

yes

depending on the DBMS used for storage

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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Recent citations in the news

Overview Of Atoti: A Python BI Analytics Tool – AIM
14 May 2021, Analytics India Magazine

FRTB product of the year: ActiveViam
28 November 2023, Risk.net

provided by Google News

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