DBMS > Google Cloud Firestore vs. Riak KV vs. Sadas Engine vs. YottaDB

System Properties Comparison Google Cloud Firestore vs. Riak KV vs. Sadas Engine vs. YottaDB

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Editorial information provided by DB-Engines

Name

Description

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.

Distributed, fault tolerant key-value store

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

A fast and solid embedded Key-value store

Primary database model

Document store

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Relational DBMS

Key-value store

Secondary database models

Relational DBMS

using the Octo plugin

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

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Score	0.20
Rank	#317	Overall
	#47	Key-value stores

Website

firebase.google.com/products/firestore

www.sadasengine.com

yottadb.com

Technical documentation

firebase.google.com/docs/firestore

www.tiot.jp/riak-docs/riak/kv/latest

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

yottadb.com/resources/documentation

Developer

Google

OpenSource, formerly Basho Technologies

SADAS s.r.l.

YottaDB, LLC

Initial release

2017

2009

2006

2001

Current release

3.2.0, December 2022

8.0

License

Commercial or Open Source

commercial

Open Source

Apache version 2, commercial enterprise edition

commercial

free trial version available

Open Source

AGPL 3.0

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

Erlang

C++

Server operating systems

hosted

Linux
OS X

AIX
Linux
Windows

Docker
Linux

Data scheme

schema-free

yes

schema-free

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

restricted

yes

SQL

Support of SQL

yes

by using the Octo plugin

APIs and other access methods

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

HTTP API
Native Erlang Interface

JDBC
ODBC
Proprietary protocol

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

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

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

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

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

Erlang

Triggers

yes, with Cloud Functions

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

selectable replication factor

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

links between data sets can be stored

yes

Transaction concepts

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

yes

optimistic locking

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.

yes

managed by 'Learn by Usage'

yes

User concepts

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.

yes, using Riak Security

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

Users and groups based on OS-security mechanisms

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More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

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