DBMS > BigObject vs. GeoMesa vs. Google Cloud Bigtable vs. Realm

System Properties Comparison BigObject vs. GeoMesa vs. Google Cloud Bigtable vs. Realm

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

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

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Spatial DBMS

Key-value store
Wide column store

Document store

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

Score	0.13
Rank	#342	Overall
	#150	Relational DBMS

Score	0.81
Rank	#214	Overall
	#4	Spatial DBMS

Score	3.58
Rank	#92	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	7.71
Rank	#52	Overall
	#9	Document stores

Website

bigobject.io

www.geomesa.org

cloud.google.com/bigtable

realm.io

Technical documentation

docs.bigobject.io

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

cloud.google.com/bigtable/docs

realm.io/docs

Developer

BigObject, Inc.

CCRi and others

Google

Realm, acquired by MongoDB in May 2019

Initial release

2015

2014

2015

2014

Current release

4.0.5, February 2024

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache License 2.0

commercial

Open Source

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

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

hosted

Android
Backend: server-less
iOS
Windows

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

SQL-like DML and DDL statements

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

Supported programming languages

C#
C++
Go
Java
JavaScript (Node.js)
Python

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

Lua

runs within the applications so server-side scripts are unnecessary

Triggers

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

none

depending on storage layer

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

depending on storage layer

Internal replication in Colossus, and regional replication between two clusters in different zones

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

depending on storage layer

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

Transaction concepts

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

Atomic single-row operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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.

yes

depending on storage layer

yes

In-Memory realm

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

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

show all

Recent citations in the news

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

What is Google Bigtable? | Definition from TechTarget
1 March 2022, TechTarget

Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs
31 January 2022, InfoQ.com

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

Google Cloud makes it cheaper to run smaller workloads on Bigtable
7 April 2020, TechCrunch

provided by Google News

Danish CEO explains Silicon Valley learning curve for European entrepreneurs - San Francisco Business Times
6 October 2016, The Business Journals

MongoDB aims to unify developer experience with launch of MongoDB Cloud
9 June 2020, diginomica

Is Swift the Future of Server-side Development?
12 September 2017, Solutions Review

Kotlin Programming Language Will Surpass Java On Android Next Year
15 October 2017, Fossbytes

Here are the winners of Nordic Startup Awards
31 May 2016, EU-Startups

provided by Google News

Share this page