DBMS > HugeGraph vs. mSQL vs. Sphinx vs. ToroDB

System Properties Comparison HugeGraph vs. mSQL vs. Sphinx vs. ToroDB

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Editorial information provided by DB-Engines

Name

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

Description

A fast-speed and highly-scalable Graph DBMS

mSQL (Mini SQL) is a simple and lightweight RDBMS

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

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

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

github.com/hugegraph
hugegraph.apache.org

hughestech.com.au/products/msql

sphinxsearch.com

github.com/torodb/server

Technical documentation

hugegraph.apache.org/docs

sphinxsearch.com/docs

Developer

Baidu

Hughes Technologies

Sphinx Technologies Inc.

8Kdata

Initial release

2018

1994

2001

2016

Current release

0.9

4.4, October 2021

3.5.1, February 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free licenses can be provided

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

Java

C++

Java

Server operating systems

Linux
macOS
Unix

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

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.

Secondary indexes

yes

also supports composite index and range index

yes

full-text index on all search fields

SQL

Support of SQL

A subset of ANSI SQL is implemented

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

SQL-like query language (SphinxQL)

APIs and other access methods

Java API
RESTful HTTP API
TinkerPop Gremlin

JDBC
ODBC

Proprietary protocol

Supported programming languages

Groovy
Java
Python

C
C++
Delphi
Java
Perl
PHP
Tcl

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

Triggers

Partitioning methods

Methods for storing different data on different nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

none

Sharding

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

none

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

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

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

User concepts

Access control

Users, roles and permissions

Access rights for users and roles

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More resources

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