DBMS > Badger vs. GeoMesa vs. H2 vs. Prometheus

System Properties Comparison Badger vs. GeoMesa vs. H2 vs. Prometheus

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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.

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

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Open-source Time Series DBMS and monitoring system

Primary database model

Secondary database models

Spatial DBMS

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

Score	0.14
Rank	#331	Overall
	#49	Key-value stores

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	8.42
Rank	#47	Overall
	#2	Time Series DBMS

Website

github.com/dgraph-io/badger

www.geomesa.org

www.h2database.com

prometheus.io

Technical documentation

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

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

www.h2database.com/html/main.html

prometheus.io/docs

Developer

DGraph Labs

CCRi and others

Thomas Mueller

Initial release

2017

2014

2005

2015

Current release

4.0.5, February 2024

2.2.220, July 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache License 2.0

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

Apache 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

Java

Server operating systems

BSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

Linux
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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.

Import of XML data possible

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

JDBC
ODBC

RESTful HTTP/JSON API

Supported programming languages

Java

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

depending on storage layer

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

depending on storage layer

With clustering: 2 database servers on different computers operate on identical copies of a database

yes

by Federation

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

Immediate Consistency

none

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

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.

depending on storage layer

yes

User concepts

Access control

yes

depending on the DBMS used for storage

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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