DBMS > LevelDB vs. MySQL vs. Solr vs. WakandaDB

System Properties Comparison LevelDB vs. MySQL vs. Solr vs. WakandaDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Widely used open source RDBMS

A widely used distributed, scalable search engine based on Apache Lucene

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Key-value store

Relational DBMS

Key/Value like access via memcached API

Search engine

Object oriented DBMS

Secondary database models

Document store
Spatial DBMS

Spatial DBMS

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

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	42.91
Rank	#24	Overall
	#3	Search engines

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

github.com/google/leveldb

www.mysql.com

solr.apache.org

wakanda.github.io

Technical documentation

github.com/google/leveldb/blob/main/doc/index.md

dev.mysql.com/doc

solr.apache.org/resources.html

wakanda.github.io/doc

Developer

Google

Oracle

since 2010, originally MySQL AB, then Sun

Apache Software Foundation

Wakanda SAS

Initial release

2011

1995

2006

2012

Current release

1.23, February 2021

8.4.0, April 2024

9.6.0, April 2024

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

BSD

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache Version 2

Open Source

AGPLv3, extended commercial license 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

C++

C and C++

Java

C++, JavaScript

Server operating systems

Illumos
Linux
OS X
Windows

FreeBSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Linux
OS X
Windows

Data scheme

schema-free

yes

Dynamic Fields enables on-the-fly addition of new fields

yes

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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

All search fields are automatically indexed

SQL

Support of SQL

yes

with proprietary extensions

Solr Parallel SQL Interface

APIs and other access methods

ADO.NET
JDBC
ODBC
Proprietary native API

Java API
RESTful HTTP/JSON API

RESTful HTTP API

Supported programming languages

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

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

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

JavaScript

Server-side scripts

Stored procedures

yes

proprietary syntax

Java plugins

yes

Triggers

yes

User configurable commands triggered on index changes

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

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

optimistic locking

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

with automatic compression on writes

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

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.