DBMS > Amazon DynamoDB vs. Oracle Berkeley DB vs. Percona Server for MongoDB vs. Postgres-XL

System Properties Comparison Amazon DynamoDB vs. Oracle Berkeley DB vs. Percona Server for MongoDB vs. Postgres-XL

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Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

Widely used in-process key-value store

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Primary database model

Document store
Key-value store

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Document store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Score	0.52
Rank	#254	Overall
	#39	Document stores

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Website

aws.amazon.com/dynamodb

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

www.percona.com/mongodb/software/percona-server-for-mongodb

www.postgres-xl.org

Technical documentation

docs.aws.amazon.com/dynamodb

docs.oracle.com/cd/E17076_05/html/index.html

docs.percona.com/percona-distribution-for-mongodb

www.postgres-xl.org/documentation

Developer

Amazon

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Percona

Initial release

2012

1994

2015

2014

since 2012, originally named StormDB

Current release

18.1.40, May 2020

3.4.10-2.10, November 2017

10 R1, October 2018

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

commercial license available

Open Source

GPL Version 2

Open Source

Mozilla public license

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, Java, C++ (depending on the Berkeley DB edition)

C++

Server operating systems

hosted

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux

Linux
macOS

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

only with the Berkeley DB XML edition

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

SQL interfaced based on SQLite is available

yes

distributed, parallel query execution

APIs and other access methods

RESTful HTTP API

proprietary protocol using JSON

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

JavaScript

user defined functions

Triggers

yes

by integration with AWS Lambda

yes

only for the SQL API

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

ACID

MVCC

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

via In-Memory Engine

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Access rights for users and roles

fine grained access rights according to SQL-standard

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