DBMS > etcd vs. Google Cloud Firestore vs. HyperSQL vs. Snowflake vs. SQLite

System Properties Comparison etcd vs. Google Cloud Firestore vs. HyperSQL vs. Snowflake vs. SQLite

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.

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

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

Widely used embeddable, in-process RDBMS

Primary database model

Key-value store

Document store

Relational DBMS

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

Score	7.03
Rank	#54	Overall
	#5	Key-value stores

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

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

firebase.google.com/products/firestore

hsqldb.org

www.snowflake.com

www.sqlite.org

Technical documentation

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

firebase.google.com/docs/firestore

hsqldb.org/web/hsqlDocsFrame.html

docs.snowflake.net/manuals/index.html

www.sqlite.org/docs.html

Developer

Google

Snowflake Computing Inc.

Dwayne Richard Hipp

Initial release

2017

2001

2014

2000

Current release

3.4, August 2019

2.7.2, June 2023

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

based on BSD license

commercial

Open Source

Public Domain

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

Server operating systems

FreeBSD
Linux
Windows

experimental

hosted

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

hosted

server-less

Data scheme

schema-free

yes

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

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-92 is not fully supported

APIs and other access methods

gRPC
JSON over HTTP

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

HTTP API

JDBC via HTTP
JDBC
ODBC

CLI Client
JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

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

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

All languages supporting JDBC/ODBC
Java

JavaScript (Node.js)
Python

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

Java, SQL

user defined functions

Triggers

yes, watching key changes

yes, with Cloud Functions

yes

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

none

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

none

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

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

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

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