DBMS > LMDB vs. MySQL vs. ObjectBox vs. Sphinx vs. Trafodion

System Properties Comparison LMDB vs. MySQL vs. ObjectBox vs. Sphinx vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

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

Widely used open source RDBMS

Extremely fast embedded database for small devices, IoT and Mobile

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

Transactional SQL-on-Hadoop DBMS

Primary database model

Key-value store

Relational DBMS

Key/Value like access via memcached API

Object oriented DBMS

Search engine

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Time Series DBMS

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

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

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	1.29
Rank	#166	Overall
	#5	Object oriented DBMS

Score	5.95
Rank	#55	Overall
	#5	Search engines

Website

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

Technical documentation

www.lmdb.tech/doc

dev.mysql.com/doc

docs.objectbox.io

sphinxsearch.com/docs

trafodion.apache.org/documentation.html

Developer

Symas

Oracle

since 2010, originally MySQL AB, then Sun

ObjectBox Limited

Sphinx Technologies Inc.

Apache Software Foundation, originally developed by HP

Initial release

2011

1995

2017

2001

2014

Current release

0.9.32, January 2024

8.4.0, April 2024

3.5.1, February 2023

2.3.0, February 2019

License

Commercial or Open Source

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache License 2.0

Open Source

GPL version 2, commercial licence available

Open Source

Apache 2.0

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.

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Implementation language

C and C++

C++

C++, Java

Server operating systems

Linux
Unix
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Android
iOS
Linux
macOS
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux

Data 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

yes

SQL

Support of SQL

yes

with proprietary extensions

SQL-like query language (SphinxQL)

yes

APIs and other access methods

ADO.NET
JDBC
ODBC
Proprietary native API

Proprietary native API

Proprietary protocol

ADO.NET
JDBC
ODBC

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

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

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

yes

proprietary syntax

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

none

Sharding

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

online/offline synchronization between client and server

none

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

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.

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 with fine-grained authorization concept

no user groups or roles

yes

fine grained access rights according to SQL-standard

More information provided by the system vendor

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