DBMS > etcd vs. GigaSpaces vs. Google Cloud Firestore vs. Microsoft Azure SQL Database vs. Microsoft SQL Server

System Properties Comparison etcd vs. GigaSpaces vs. Google Cloud Firestore vs. Microsoft Azure SQL Database vs. Microsoft SQL Server

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.

Database as a Service offering with high compatibility to Microsoft SQL Server

Microsofts flagship relational DBMS

Primary database model

Key-value store

Document store
Object oriented DBMS

Values are user defined objects

Document store

Relational DBMS

Secondary database models

Graph DBMS
Search engine

Document store
Graph DBMS
Spatial DBMS

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

Score	7.25
Rank	#54	Overall
	#5	Key-value stores

Score	0.97
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Website

etcd.io
github.com/etcd-io/etcd

www.gigaspaces.com

firebase.google.com/products/firestore

azure.microsoft.com/en-us/products/azure-sql/database

www.microsoft.com/en-us/sql-server

Technical documentation

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

docs.gigaspaces.com/latest/landing.html

firebase.google.com/docs/firestore

docs.microsoft.com/en-us/azure/azure-sql

learn.microsoft.com/en-US/sql/sql-server

Developer

Gigaspaces Technologies

Google

Microsoft

Initial release

2000

2017

2010

1989

Current release

3.4, August 2019

15.5, September 2020

V12

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2; Commercial licenses available

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, C++, .Net

C++

Server operating systems

FreeBSD
Linux
Windows

experimental

Linux
macOS
Solaris
Windows

hosted

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.

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

gRPC
JSON over HTTP

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

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

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Supported programming languages

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

.Net
C++
Java
Python
Scala

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

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Server-side scripts

Stored procedures

yes

yes, Firebase Rules & Cloud Functions

Transact SQL

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes, watching key changes

yes, event driven architecture

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

Replication methods

Methods for redundantly storing data on multiple nodes

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

Multi-source replication

yes, with always 3 replicas available

yes, but depending on the SQL-Server Edition

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

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.

fine grained access rights according to SQL-standard

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