DBMS > Amazon DocumentDB vs. Bangdb vs. Oracle Berkeley DB vs. VelocityDB

System Properties Comparison Amazon DocumentDB vs. Bangdb vs. Oracle Berkeley DB vs. VelocityDB

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Editorial information provided by DB-Engines

Name

Description

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

Converged and high performance database for device data, events, time series, document and graph

Widely used in-process key-value store

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Document store

Document store
Graph DBMS
Time Series DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Graph DBMS
Object oriented DBMS

Secondary database models

Spatial DBMS

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

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

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

Score	0.05
Rank	#358	Overall
	#36	Graph DBMS
	#16	Object oriented DBMS

Website

aws.amazon.com/documentdb

bangdb.com

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

velocitydb.com

Technical documentation

aws.amazon.com/documentdb/resources

docs.bangdb.com

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

velocitydb.com/UserGuide

Developer

Sachin Sinha, BangDB

Oracle

originally developed by Sleepycat, which was acquired by Oracle

VelocityDB Inc

Initial release

2019

2012

1994

2011

Current release

BangDB 2.0, October 2021

18.1.40, May 2020

7.x

License

Commercial or Open Source

commercial

Open Source

BSD 3

Open Source

commercial license available

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, C++

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

Server operating systems

hosted

Linux

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Any that supports .NET

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

yes: string, long, double, int, geospatial, stream, events

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

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

yes

SQL interfaced based on SQLite is available

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

Proprietary protocol
RESTful HTTP API

.Net

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

C
C#
C++
Java
Python

.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

.Net

Server-side scripts

Stored procedures

Triggers

yes, Notifications (with Streaming only)

yes

only for the SQL API

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

selectable replication factor, Knob for CAP (enterprise version only)

Source-replica replication

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

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

Transaction concepts

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

Atomic single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes, run db with in-memory only mode

yes

User concepts

Access control

Access rights for users and roles

yes (enterprise version only)

Based on Windows Authentication

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