DBMS > Amazon DocumentDB vs. Drizzle vs. LevelDB vs. Oracle Rdb

System Properties Comparison Amazon DocumentDB vs. Drizzle vs. LevelDB vs. Oracle Rdb

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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

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

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

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

Primary database model

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

Score	1.91
Rank	#132	Overall
	#24	Document stores

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

Score	1.08
Rank	#184	Overall
	#85	Relational DBMS

Website

aws.amazon.com/documentdb

github.com/google/leveldb

www.oracle.com/database/technologies/related/rdb.html

Technical documentation

aws.amazon.com/documentdb/resources

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

www.oracle.com/database/technologies/related/rdb-doc.html

Developer

Drizzle project, originally started by Brian Aker

Google

Oracle, originally developed by Digital Equipment Corporation (DEC)

Initial release

2019

2008

2011

1984

Current release

7.2.4, September 2012

1.23, February 2021

7.4.1.1, 2021

License

Commercial or Open Source

commercial

Open Source

GNU GPL

Open Source

BSD

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Server operating systems

hosted

FreeBSD
Linux
OS X

Illumos
Linux
OS X
Windows

HP Open VMS

Data scheme

schema-free

yes

schema-free

Flexible Schema (defined schema, partial schema, schema free)

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

yes

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

JDBC

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

C
C++
Java
PHP

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

Server-side scripts

Stored procedures

Triggers

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

Transaction concepts

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

Atomic single-document operations

ACID

yes, on a single node

Concurrency

Support for concurrent manipulation of data

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.

User concepts

Access control

Access rights for users and roles

Pluggable authentication mechanisms

e.g. LDAP, HTTP

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