DBMS > Lovefield vs. mSQL vs. Postgres-XL vs. Sphinx vs. ToroDB

System Properties Comparison Lovefield vs. mSQL vs. Postgres-XL vs. Sphinx vs. ToroDB

Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Embeddable relational database for web apps written in pure JavaScript

mSQL (Mini SQL) is a simple and lightweight RDBMS

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Open source search engine for searching in data from different sources, e.g. relational databases

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Relational DBMS

Search engine

Document store

Secondary database models

Document store
Spatial DBMS

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

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

google.github.io/lovefield

hughestech.com.au/products/msql

www.postgres-xl.org

sphinxsearch.com

github.com/torodb/server

Technical documentation

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

www.postgres-xl.org/documentation

sphinxsearch.com/docs

Developer

Google

Hughes Technologies

Sphinx Technologies Inc.

8Kdata

Initial release

2014

1994

2014

since 2012, originally named StormDB

2001

2016

Current release

2.1.12, February 2017

4.4, October 2021

10 R1, October 2018

3.5.1, February 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

free licenses can be provided

Open Source

Mozilla public license

Open Source

GPL version 2, commercial licence available

Open Source

AGPL-V3

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

JavaScript

C++

Java

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
macOS

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

All OS with a Java 7 VM

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, boolean, date, object_id

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

XML type, but no XML query functionality

Secondary indexes

yes

full-text index on all search fields

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

distributed, parallel query execution

SQL-like query language (SphinxQL)

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Proprietary protocol

Supported programming languages

JavaScript

C
C++
Delphi
Java
Perl
PHP
Tcl

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

user defined functions

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Sharding

Partitioning is done manually, search queries against distributed index is supported

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

MVCC

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

The original contents of fields are not stored in the Sphinx index.

yes

In-memory capabilities

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

yes

using MemoryDB

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles

More information provided by the system vendor

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