DBMS > GeoMesa vs. Google Cloud Firestore vs. JaguarDB vs. SpaceTime vs. Vitess

System Properties Comparison GeoMesa vs. Google Cloud Firestore vs. JaguarDB vs. SpaceTime vs. Vitess

Editorial information provided by DB-Engines

Name

Description

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

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

SpaceTime is a spatio-temporal DBMS with a focus on performance.

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Spatial DBMS

Document store

Key-value store
Vector DBMS

Spatial DBMS

Relational DBMS

Secondary database models

Relational DBMS

Document store
Spatial DBMS

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

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

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
	#7	Spatial DBMS

Score	0.82
Rank	#209	Overall
	#97	Relational DBMS

Website

www.geomesa.org

firebase.google.com/products/firestore

www.jaguardb.com

www.mireo.com/spacetime

vitess.io

Technical documentation

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

firebase.google.com/docs/firestore

www.jaguardb.com/support.html

vitess.io/docs

Developer

CCRi and others

Google

DataJaguar, Inc.

Mireo

The Linux Foundation, PlanetScale

Initial release

2014

2017

2015

2020

2013

Current release

4.0.5, February 2024

3.3 July 2023

15.0.2, December 2022

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Open Source

GPL V3.0

commercial

Open Source

Apache Version 2.0, commercial licenses 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

Scala

C++

the server part. Clients available in other languages

C++

Server operating systems

hosted

Linux

Docker
Linux
macOS

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

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

SQL

Support of SQL

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

A subset of ANSI SQL is implemented

yes

with proprietary extensions

APIs and other access methods

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

JDBC
ODBC

RESTful HTTP API

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

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

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

C#
C++
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

yes

proprietary syntax

Triggers

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

Sharding

Fixed-grid hypercubes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

Multi-source replication

Real-time block device replication (DRBD)

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

depending on storage layer

Immediate Consistency

Eventual Consistency

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

yes

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

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

yes

Users with fine-grained authorization concept

no user groups or roles

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

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

show all

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

show all

Recent citations in the 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

PlanetScale Unveils Distributed MySQL Database Service Based on Vitess
18 May 2021, Datanami

PlanetScale grabs YouTube-developed open-source tech, promises Vitess DBaaS with on-the-fly schema changes
18 May 2021, The Register

With Vitess 4.0, database vendor matures cloud-native platform
13 November 2019, TechTarget

Massively Scaling MySQL Using Vitess
19 February 2019, InfoQ.com

They scaled YouTube -- now they’ll shard everyone with PlanetScale
13 December 2018, TechCrunch

provided by Google News

Share this page