DBMS > Blueflood vs. LMDB vs. mSQL vs. MySQL vs. Sphinx

System Properties Comparison Blueflood vs. LMDB vs. mSQL vs. MySQL vs. Sphinx

Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

A high performant, light-weight, embedded key-value database library

mSQL (Mini SQL) is a simple and lightweight RDBMS

Widely used open source RDBMS

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

Primary database model

Time Series DBMS

Key-value store

Relational DBMS

Key/Value like access via memcached API

Search engine

Secondary database models

Document store
Spatial DBMS

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

Score	0.13
Rank	#346	Overall
	#33	Time Series DBMS

Score	2.09
Rank	#121	Overall
	#20	Key-value stores

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	5.95
Rank	#55	Overall
	#5	Search engines

Website

blueflood.io

www.symas.com/symas-embedded-database-lmdb

hughestech.com.au/products/msql

www.mysql.com

sphinxsearch.com

Technical documentation

github.com/rax-maas/blueflood/wiki

www.lmdb.tech/doc

dev.mysql.com/doc

sphinxsearch.com/docs

Developer

Rackspace

Symas

Hughes Technologies

Oracle

since 2010, originally MySQL AB, then Sun

Sphinx Technologies Inc.

Initial release

2013

2011

1994

1995

2001

Current release

0.9.32, January 2024

4.4, October 2021

8.4.0, April 2024

3.5.1, February 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

commercial

free licenses can be provided

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

GPL version 2, commercial licence available

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.

Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.

Implementation language

Java

C and C++

C++

Server operating systems

Linux
OS X

Linux
Unix
Windows

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

FreeBSD
Linux
OS X
Solaris
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

predefined scheme

schema-free

yes

Typing

predefined data types such as float or date

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.

yes

Secondary indexes

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

yes

with proprietary extensions

SQL-like query language (SphinxQL)

APIs and other access methods

HTTP REST

JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Proprietary protocol

Supported programming languages

.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl

C
C++
Delphi
Java
Perl
PHP
Tcl

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

none

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

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

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 with fine-grained authorization concept

no user groups or roles

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.