DBMS > GigaSpaces vs. Google Cloud Firestore vs. Sadas Engine vs. Snowflake

System Properties Comparison GigaSpaces vs. Google Cloud Firestore vs. Sadas Engine vs. Snowflake

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Editorial information provided by DB-Engines

Name

Description

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

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

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Document store
Object oriented DBMS

Values are user defined objects

Document store

Relational DBMS

Secondary database models

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Score	1.02
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	8.96
Rank	#48	Overall
	#8	Document stores

Score	0.03
Rank	#379	Overall
	#156	Relational DBMS

Score	123.20
Rank	#9	Overall
	#6	Relational DBMS

Website

www.gigaspaces.com

firebase.google.com/products/firestore

www.sadasengine.com

www.snowflake.com

Technical documentation

docs.gigaspaces.com/latest/landing.html

firebase.google.com/docs/firestore

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

docs.snowflake.net/manuals/index.html

Developer

Gigaspaces Technologies

Google

SADAS s.r.l.

Snowflake Computing Inc.

Initial release

2000

2017

2006

2014

Current release

15.5, September 2020

8.0

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial licenses available

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++, .Net

C++

Server operating systems

Linux
macOS
Solaris
Windows

hosted

AIX
Linux
Windows

hosted

Data scheme

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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.

XML can be used for describing objects metadata

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-99 for query and DML statements

yes

APIs and other access methods

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

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

JDBC
ODBC
Proprietary protocol

CLI Client
JDBC
ODBC

Supported programming languages

.Net
C++
Java
Python
Scala

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

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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

yes, Firebase Rules & Cloud Functions

user defined functions

Triggers

yes, event driven architecture

yes, with Cloud Functions

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

Multi-source replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

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 capabilities

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

yes

managed by 'Learn by Usage'

User concepts

Access control

Role-based 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

Users with fine-grained authorization concept, user roles and pluggable authentication

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