DBMS > Badger vs. Google Cloud Firestore vs. HugeGraph vs. Sadas Engine vs. Yaacomo

System Properties Comparison Badger vs. Google Cloud Firestore vs. HugeGraph vs. Sadas Engine vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

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.

A fast-speed and highly-scalable Graph DBMS

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

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

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

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Website

github.com/dgraph-io/badger

firebase.google.com/products/firestore

github.com/hugegraph
hugegraph.apache.org

www.sadasengine.com

yaacomo.com

Technical documentation

godoc.org/github.com/dgraph-io/badger

firebase.google.com/docs/firestore

hugegraph.apache.org/docs

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

Developer

DGraph Labs

Google

Baidu

SADAS s.r.l.

Q2WEB GmbH

Initial release

2017

2018

2006

2009

Current release

0.9

8.0

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Apache Version 2.0

commercial

free trial version available

commercial

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

Java

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

hosted

Linux
macOS
Unix

AIX
Linux
Windows

Android
Linux
Windows

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

also supports composite index and range index

yes

SQL

Support of SQL

yes

APIs and other access methods

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

Java API
RESTful HTTP API
TinkerPop Gremlin

JDBC
ODBC
Proprietary protocol

JDBC
ODBC

Supported programming languages

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

Groovy
Java
Python

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

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

asynchronous Gremlin script jobs

Triggers

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

depending on used storage backend, e.g. Cassandra and HBase

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

yes

depending on used storage backend, e.g. Cassandra and HBase

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

Transaction concepts

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

yes

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.

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.

Users, roles and permissions

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

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

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

show all

Recent citations in the news

Realtime vs Cloud Firestore: Which Firebase Database to go?
8 March 2024, Appinventiv

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

Google launches Cloud Firestore, a new document database for app developers
3 October 2017, TechCrunch

Google's Cloud-Native NoSQL Database Cloud Firestore Is Now Generally Available
8 February 2019, InfoQ.com

Firestore and Python | NoSQL on Google Cloud
7 August 2020, Towards Data Science

provided by Google News

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23 April 2024, GBHackers

provided by Google News

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