DBMS > GeoMesa vs. Google Cloud Datastore vs. JaguarDB vs. Linter

System Properties Comparison GeoMesa vs. Google Cloud Datastore vs. JaguarDB vs. Linter

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

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

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

Performant, highly scalable DBMS for AI and IoT applications

RDBMS for high security requirements

Primary database model

Spatial DBMS

Document store

Key-value store
Vector DBMS

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	4.36
Rank	#72	Overall
	#12	Document stores

Score	0.06
Rank	#381	Overall
	#59	Key-value stores
	#14	Vector DBMS

Score	0.12
Rank	#350	Overall
	#152	Relational DBMS

Website

www.geomesa.org

cloud.google.com/datastore

www.jaguardb.com

linter.ru

Technical documentation

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

cloud.google.com/datastore/docs

www.jaguardb.com/support.html

Developer

CCRi and others

Google

DataJaguar, Inc.

relex.ru

Initial release

2014

2008

2015

1990

Current release

5.0.0, May 2024

3.3 July 2023

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Open Source

GPL V3.0

commercial

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 and C++

Server operating systems

hosted

Linux

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, details here

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

SQL-like query language (GQL)

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

APIs and other access methods

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

JDBC
ODBC

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

Supported programming languages

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

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

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

Server-side scripts

Stored procedures

using Google App Engine

yes

proprietary syntax with the possibility to convert from PL/SQL

Triggers

Callbacks using the Google Apps Engine

yes

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

Multi-source replication using Paxos

Multi-source replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

depending on storage layer

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

ACID

Concurrency

Support for concurrent manipulation of data

yes

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

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 (IAM)

rights management via user accounts

fine grained access rights according to SQL-standard

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

Recent citations in the news

Google Cloud Platform: Professional Data Engineer certification prep
11 June 2024, oreilly.com

Google Cloud Stops Exit Fees
12 January 2024, Spiceworks News and Insights

Best cloud storage of 2024
4 June 2024, TechRadar

BigID Data Intelligence Platform Now Available on Google Cloud Marketplace
6 November 2023, PR Newswire

Google says it'll stop charging fees to transfer data out of Google Cloud
11 January 2024, TechCrunch

provided by Google News

Share this page