DBMS > Couchbase vs. Google Cloud Firestore vs. Sadas Engine vs. TerminusDB

System Properties Comparison Couchbase vs. Google Cloud Firestore vs. Sadas Engine vs. TerminusDB

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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 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.

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Document store

Relational DBMS

Graph 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

Document store
RDF store

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

Score	16.74
Rank	#33	Overall
	#5	Document stores

Score	6.63
Rank	#54	Overall
	#9	Document stores

Score	0.00
Rank	#385	Overall
	#159	Relational DBMS

Score	0.19
Rank	#311	Overall
	#27	Graph DBMS

Website

www.couchbase.com

firebase.google.com/products/firestore

www.sadasengine.com

terminusdb.com

Technical documentation

docs.couchbase.com

firebase.google.com/docs/firestore

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

terminusdb.github.io/terminusdb/#

Developer

Couchbase, Inc.

Google

SADAS s.r.l.

DataChemist Ltd.

Initial release

2011

2017

2006

2018

Current release

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

8.0

11.0.0, January 2023

License

Commercial or Open Source

Open Source

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

commercial

free trial version available

Open Source

GPL V3

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

C++

Prolog, Rust

Server operating systems

Linux
OS X
Windows

hosted

AIX
Linux
Windows

Linux

Data scheme

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

yes

SQL-like query language (WOQL)

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

JDBC
ODBC
Proprietary protocol

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

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

.Net
C
C#
C++
Groovy
Java
PHP
Python

JavaScript
Python

Server-side scripts

Stored procedures

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

yes, Firebase Rules & Cloud Functions

yes

Triggers

yes

via the TAP protocol

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

Sharding

horizontal partitioning

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

Multi-source replication

none

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory journaling

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Ephemeral buckets

yes

managed by 'Learn by Usage'

User concepts

Access control

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

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

Access rights for users, groups and roles according to SQL-standard

Role-based access control

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