DBMS > GeoSpock vs. H2GIS vs. NSDb

System Properties Comparison GeoSpock vs. H2GIS vs. NSDb

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Spatial and temporal data processing engine for extreme data scale

Spatial extension of H2

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

Primary database model

Relational DBMS

Spatial DBMS

Time Series DBMS

Secondary database models

Time Series DBMS

Relational DBMS

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

Score	0.38
Rank	#324	Overall
	#144	Relational DBMS

Score	0.25
Rank	#358	Overall
	#5	Spatial DBMS

Score	0.17
Rank	#378	Overall
	#39	Time Series DBMS

Website

geospock.com

www.h2gis.org

nsdb.io

Technical documentation

docs.geospock.com/Content/Home.htm

www.h2gis.org/docs/home

nsdb.io/Architecture

Developer

GeoSpock

CNRS

Initial release

2013

2017

Current release

2.0, September 2019

License

Commercial or Open Source

commercial

Open Source

LGPL 3.0

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java, Javascript

Java

Java, Scala

Server operating systems

hosted

Linux
macOS

Data scheme

yes

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

temporal, categorical

yes

all fields are automatically indexed

SQL

Support of SQL

ANSI SQL for query only (using Presto)

yes

SQL-like query language

APIs and other access methods

JDBC

gRPC
HTTP REST
WebSocket

Supported programming languages

Java

Java
Scala

Server-side scripts

Stored procedures

yes

based on H2

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

based on H2

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

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

Using Apache Lucene

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access rights for users can be defined per table

yes

based on H2

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

GeoSpock’s extreme-scale data mission in $5.4m funding boost
8 October 2020, Cambridge Independent

Jet-heeled GeoSpock joins Vodafone backed tech venture
28 October 2020, Business Weekly

Mosaic Therapeutics Closes $28M Series A Funding
4 April 2023, FinSMEs

Japanese tech company joins GeoSpock’s new $5.4m round
2 October 2020, Business Weekly

GeoSpock: making extreme data easy
21 March 2019, Land Mobile magazine

provided by Google News

Share this page