DBMS > GeoSpock vs. Google Cloud Firestore vs. JaguarDB vs. NSDb vs. OpenQM

System Properties Comparison GeoSpock vs. Google Cloud Firestore vs. JaguarDB vs. NSDb vs. OpenQM

Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

Spatial and temporal data processing engine for extreme data scale

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

Performant, highly scalable DBMS for AI and IoT applications

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

QpenQM is a high-performance, self-tuning, multi-value DBMS

Primary database model

Relational DBMS

Document store

Key-value store
Vector DBMS

Time Series DBMS

Multivalue DBMS

Secondary database models

Time Series DBMS

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

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Website

geospock.com

firebase.google.com/products/firestore

www.jaguardb.com

nsdb.io

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

Technical documentation

firebase.google.com/docs/firestore

www.jaguardb.com/support.html

nsdb.io/Architecture

Developer

GeoSpock

Google

DataJaguar, Inc.

Rocket Software, originally Martin Phillips

Initial release

2017

2015

2017

1993

Current release

2.0, September 2019

3.3 July 2023

3.4-12

License

Commercial or Open Source

commercial

Open Source

GPL V3.0

Open Source

Apache Version 2.0

Open Source

GPLv2, extended commercial license available

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

C++

the server part. Clients available in other languages

Java, Scala

Server operating systems

hosted

Linux

Linux
macOS

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Data scheme

yes

schema-free

yes

with some exceptions

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.

yes

Secondary indexes

temporal, categorical

yes

all fields are automatically indexed

yes

SQL

Support of SQL

ANSI SQL for query only (using Presto)

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

SQL-like query language

APIs and other access methods

JDBC

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

JDBC
ODBC

gRPC
HTTP REST
WebSocket

Supported programming languages

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Java
Scala

.Net
Basic
C
Java
Objective C
PHP
Python

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

yes

Triggers

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

yes

In-memory capabilities

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

User concepts

Access control

Access rights for users can be defined per table

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

rights management via user accounts

Access rights can be defined down to the item level

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Related products and services

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More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

show all

Recent citations in the news

GeoSpock launches Spatial Big Data Platform 2.0
4 September 2019, VanillaPlus

nChain leads investment round in extreme-scale data firm GeoSpock
2 October 2020, CoinGeek

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

Big data processing techniques to streamline analytics
5 October 2018, TechTarget

Ola acquires GeoSpoc to build next-gen location technology
5 October 2021, The Economic Times

provided by Google News

Google's AI-First Strategy Brings Vector Support To Cloud Databases
1 March 2024, Forbes

Realtime vs Cloud Firestore: Which Firebase Database to go?
8 March 2024, Appinventiv

Google's Cloud Firestore is now generally available
31 January 2019, ZDNet

Google launches Cloud Firestore, a new document database for app developers
3 October 2017, TechCrunch

Google's Cloud-Native NoSQL Database Cloud Firestore Is Now Generally Available
8 February 2019, InfoQ.com

provided by Google News

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