DBMS > Couchbase vs. Firebase Realtime Database vs. GeoMesa vs. Google Cloud Bigtable vs. Graphite

System Properties Comparison Couchbase vs. Firebase Realtime Database vs. GeoMesa vs. Google Cloud Bigtable vs. Graphite

Editorial information provided by DB-Engines

Name

Description

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

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.

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Primary database model

Document store

Spatial DBMS

Key-value store
Wide column store

Time Series DBMS

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

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

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	4.57
Rank	#73	Overall
	#5	Time Series DBMS

Website

www.couchbase.com

firebase.google.com/products/realtime-database

www.geomesa.org

cloud.google.com/bigtable

github.com/graphite-project/graphite-web

Technical documentation

docs.couchbase.com

firebase.google.com/docs/database

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

cloud.google.com/bigtable/docs

graphite.readthedocs.io

Developer

Couchbase, Inc.

Google

acquired by Google 2014

CCRi and others

Google

Chris Davis

Initial release

2011

2012

2014

2015

2006

Current release

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

4.0.5, February 2024

License

Commercial or Open Source

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

commercial

Open Source

Apache License 2.0

commercial

Open Source

Apache 2.0

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

C, C++, Go and Erlang

Scala

Python

Server operating systems

Linux
OS X
Windows

hosted

Linux
Unix

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

APIs and other access methods

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

Android
iOS
JavaScript API
RESTful HTTP API

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

HTTP API
Sockets

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

Java
JavaScript
Objective-C

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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

limited functionality with using 'rules'

Triggers

yes

via the TAP protocol

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

depending on storage layer

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

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

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

depending on storage layer

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

none

Foreign keys

Referential integrity

Transaction concepts

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

ACID

yes

Atomic single-row operations

Concurrency

Support for concurrent manipulation of data

yes

locking

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

Ephemeral buckets

depending on storage layer

User concepts

Access control

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

yes, based on authentication and database rules

yes

depending on the DBMS used for storage

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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