DBMS > GeoMesa vs. Google Cloud Datastore vs. IRONdb vs. WakandaDB

System Properties Comparison GeoMesa vs. Google Cloud Datastore vs. IRONdb vs. WakandaDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

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

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

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

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

www.geomesa.org

cloud.google.com/datastore

www.circonus.com/solutions/time-series-database/

wakanda.github.io

Technical documentation

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

cloud.google.com/datastore/docs

docs.circonus.com/irondb/category/getting-started

wakanda.github.io/doc

Developer

CCRi and others

Google

Circonus LLC.

Wakanda SAS

Initial release

2014

2008

2017

2012

Current release

4.0.5, February 2024

V0.10.20, January 2018

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Open Source

AGPLv3, 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

Scala

C and C++

C++, JavaScript

Server operating systems

hosted

Linux

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, details here

yes

text, numeric, histograms

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)

SQL-like query language (Circonus Analytics Query Language: CAQL)

APIs and other access methods

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

HTTP API

RESTful HTTP API

Supported programming languages

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

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

JavaScript

Server-side scripts

Stored procedures

using Google App Engine

yes, in Lua

yes

Triggers

Callbacks using the Google Apps Engine

yes

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

Sharding

Automatic, metric affinity per node

none

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

Multi-source replication using Paxos

configurable replication factor, datacenter aware

none

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.

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

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)

yes

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

Best cloud storage of 2024
29 April 2024, TechRadar

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

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

What is Google App Engine? | Definition from TechTarget
26 April 2024, TechTarget

What Is Google Cloud Platform?
28 August 2023, Simplilearn

provided by Google News

Application observability firm Apica buys telemetry data startup Circonus and adds more funding
21 February 2024, SiliconANGLE News

Apica Acquires Telemetry Data Management Pioneer Circonus And Lands New Funding
22 February 2024, Datanami

Apica gets $6 million in funding and buys Circonus -
21 February 2024, Enterprise Times

provided by Google News

Share this page