DBMS > GeoMesa vs. gStore vs. NSDb

System Properties Comparison GeoMesa vs. gStore vs. NSDb

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Editorial information provided by DB-Engines

Name

Description

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

A native Graph DBMS to store and maintain very large RDF datasets.

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Primary database model

Spatial DBMS

Graph DBMS
RDF store

Time Series DBMS

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

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	0.04
Rank	#359	Overall
	#37	Graph DBMS
	#18	RDF stores

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

www.geomesa.org

en.gstore.cn

nsdb.io

Technical documentation

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

en.gstore.cn/#/enDocs

nsdb.io/Architecture

Developer

CCRi and others

Initial release

2014

2016

2017

Current release

4.0.5, February 2024

1.2, November 2023

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

BSD

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

Scala

C++

Java, Scala

Server operating systems

Linux

Linux
macOS

Data scheme

yes

schema-free and OWL/RDFS-schema support

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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

all fields are automatically indexed

SQL

Support of SQL

SQL-like query language

APIs and other access methods

HTTP API
SPARQL 1.1

gRPC
HTTP REST
WebSocket

Supported programming languages

C++
Java
JavaScript (Node.js)
PHP
Python

Java
Scala

Server-side scripts

Stored procedures

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

Sharding

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

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

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

Users, roles and permissions, Role-Based Access Control (RBAC) supported

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