DBMS > Drizzle vs. RocksDB vs. WakandaDB

System Properties Comparison Drizzle vs. RocksDB vs. WakandaDB

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

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

Primary database model

Relational DBMS

Key-value store

Object oriented DBMS

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

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

rocksdb.org

wakanda.github.io

Technical documentation

github.com/facebook/rocksdb/wiki

wakanda.github.io/doc

Developer

Drizzle project, originally started by Brian Aker

Facebook, Inc.

Wakanda SAS

Initial release

2008

2013

2012

Current release

7.2.4, September 2012

8.11.4, April 2024

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

BSD

Open Source

AGPLv3, extended commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C++, JavaScript

Server operating systems

FreeBSD
Linux
OS X

Linux

Linux
OS X
Windows

Data scheme

yes

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.

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

APIs and other access methods

JDBC

C++ API
Java API

RESTful HTTP API

Supported programming languages

C
C++
Java
PHP

C
C++
Go
Java
Perl
Python
Ruby

JavaScript

Server-side scripts

Stored procedures

yes

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

yes

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