DBMS > Lovefield vs. mSQL vs. OrigoDB vs. Snowflake vs. Spark SQL

System Properties Comparison Lovefield vs. mSQL vs. OrigoDB vs. Snowflake vs. Spark SQL

Editorial information provided by DB-Engines

Name

Description

Embeddable relational database for web apps written in pure JavaScript

mSQL (Mini SQL) is a simple and lightweight RDBMS

A fully ACID in-memory object graph database

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

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Relational DBMS

Document store
Object oriented DBMS

Relational DBMS

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

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Website

google.github.io/lovefield

hughestech.com.au/products/msql

origodb.com

www.snowflake.com

spark.apache.org/sql

Technical documentation

github.com/google/lovefield/blob/master/docs/spec_index.md

origodb.com/docs

docs.snowflake.net/manuals/index.html

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Google

Hughes Technologies

Robert Friberg et al

Snowflake Computing Inc.

Apache Software Foundation

Initial release

2014

1994

2009

under the name LiveDB

2014

Current release

2.1.12, February 2017

4.4, October 2021

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

free licenses can be provided

Open Source

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

JavaScript

Scala

Server operating systems

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

tested with Chrome, Firefox, IE, Safari

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

Linux
Windows

hosted

Linux
OS X
Windows

Data scheme

yes

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

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

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

A subset of ANSI SQL is implemented

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

yes

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC

.NET Client API
HTTP API
LINQ

CLI Client
JDBC
ODBC

JDBC
ODBC

Supported programming languages

JavaScript

C
C++
Delphi
Java
Perl
PHP
Tcl

.Net

JavaScript (Node.js)
Python

Java
Python
R
Scala

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

Using read-only observers

yes

Domain Events

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

client side managed; servers are not synchronized

yes

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

depending on model

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

Write ahead log

yes

In-memory capabilities

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

yes

using MemoryDB

yes

User concepts

Access control

Role based authorization

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

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