DBMS > Badger vs. chDB vs. GeoMesa

System Properties Comparison Badger vs. chDB vs. GeoMesa

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Editorial information provided by DB-Engines

Name

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

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

Key-value store

Relational DBMS

Spatial DBMS

Secondary database models

Time Series DBMS

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

Score	0.14
Rank	#328	Overall
	#48	Key-value stores

Score	0.05
Rank	#358	Overall
	#152	Relational DBMS

Score	0.78
Rank	#214	Overall
	#4	Spatial DBMS

Website

github.com/dgraph-io/badger

github.com/chdb-io/chdb

www.geomesa.org

Technical documentation

godoc.org/github.com/dgraph-io/badger

doc.chdb.io

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

Developer

DGraph Labs

CCRi and others

Initial release

2017

2023

2014

Current release

5.0.1, July 2024

License

Commercial or Open Source

Open Source

Apache 2.0

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

Scala

Server operating systems

BSD
Linux
OS X
Solaris
Windows

server-less

Data scheme

schema-free

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

Close to ANSI SQL (SQL/JSON + extensions)

Supported programming languages

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

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

depending on storage layer

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

none

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

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

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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