DBMS > Badger vs. GeoMesa vs. PouchDB vs. Spark SQL vs. STSdb

System Properties Comparison Badger vs. GeoMesa vs. PouchDB vs. Spark SQL vs. STSdb

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.

JavaScript DBMS with an API inspired by CouchDB

Spark SQL is a component on top of 'Spark Core' for structured data processing

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

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

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Website

github.com/dgraph-io/badger

www.geomesa.org

pouchdb.com

spark.apache.org/sql

github.com/STSSoft/STSdb4

Technical documentation

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

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

pouchdb.com/guides

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

DGraph Labs

CCRi and others

Apache Software Foundation

STS Soft SC

Initial release

2017

2014

2012

2014

2011

Current release

5.0.0, May 2024

7.1.1, June 2019

3.5.0 ( 2.13), September 2023

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache License 2.0

Open Source

Apache 2.0

Open Source

GPLv2, commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Scala

JavaScript

Scala

Server operating systems

BSD
Linux
OS X
Solaris
Windows

server-less, requires a JavaScript environment (browser, Node.js)

Linux
OS X
Windows

Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

via views

SQL

Support of SQL

SQL-like DML and DDL statements

APIs and other access methods

HTTP REST

only for PouchDB Server
JavaScript API

JDBC
ODBC

.NET Client API

Supported programming languages

JavaScript

Java
Python
R
Scala

C#
Java

Server-side scripts

Stored procedures

View functions in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

depending on storage layer

Sharding

with a proxy-based framework, named couchdb-lounge

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

depending on storage layer

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

none

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

Eventual Consistency

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

by using IndexedDB, WebSQL or LevelDB as backend

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

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

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