DBMS > etcd vs. Google BigQuery vs. mSQL vs. OrigoDB vs. SQL.JS

System Properties Comparison etcd vs. Google BigQuery vs. mSQL vs. OrigoDB vs. SQL.JS

Editorial information provided by DB-Engines

Name

Description

A distributed reliable key-value store

Large scale data warehouse service with append-only tables

mSQL (Mini SQL) is a simple and lightweight RDBMS

A fully ACID in-memory object graph database

Port of SQLite to JavaScript

Primary database model

Key-value store

Relational DBMS

Document store
Object oriented DBMS

Relational DBMS

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

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	0.53
Rank	#252	Overall
	#116	Relational DBMS

Website

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

cloud.google.com/bigquery

hughestech.com.au/products/msql

origodb.com

sql.js.org

Technical documentation

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

cloud.google.com/bigquery/docs

origodb.com/docs

sql.js.org/documentation/index.html

Developer

Google

Hughes Technologies

Robert Friberg et al

Alon Zakai

enhancements implemented by others

Initial release

2010

1994

2009

under the name LiveDB

2012

Current release

3.4, August 2019

4.4, October 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free licenses can be provided

Open Source

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

JavaScript

Server operating systems

FreeBSD
Linux
Windows

experimental

hosted

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
Windows

server-less, requires a JavaScript environment (browser, Node.js)

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

yes

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

yes

SQL-92 is not fully supported

APIs and other access methods

gRPC
JSON over HTTP

RESTful HTTP/JSON API

JDBC
ODBC

.NET Client API
HTTP API
LINQ

JavaScript API

Supported programming languages

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

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C++
Delphi
Java
Perl
PHP
Tcl

.Net

JavaScript

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Triggers

yes, watching key changes

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

client side managed; servers are not synchronized

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.

none

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Foreign keys

Referential integrity

depending on model

yes

Transaction concepts

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

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

except by serializing a db to a file

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 privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Role based authorization

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