DBMS > Amazon DocumentDB vs. Bangdb vs. Riak TS vs. VoltDB

System Properties Comparison Amazon DocumentDB vs. Bangdb vs. Riak TS vs. VoltDB

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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

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Document store

Document store
Graph DBMS
Time Series DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	1.91
Rank	#131	Overall
	#24	Document stores

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

aws.amazon.com/documentdb

bangdb.com

www.voltdb.com

Technical documentation

aws.amazon.com/documentdb/resources

docs.bangdb.com

www.tiot.jp/riak-docs/riak/ts/latest

docs.voltdb.com

Developer

Sachin Sinha, BangDB

Open Source, formerly Basho Technologies

VoltDB Inc.

Initial release

2019

2012

2015

2010

Current release

BangDB 2.0, October 2021

3.0.0, September 2022

11.3, April 2022

License

Commercial or Open Source

commercial

Open Source

BSD 3

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

Erlang

Java, C++

Server operating systems

hosted

Linux

Linux
OS X

for development

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.

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

restricted

yes

SQL

Support of SQL

SQL like support with command line tool

yes, limited

yes

only a subset of SQL 99

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

Proprietary protocol
RESTful HTTP API

HTTP API
Native Erlang Interface

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

C
C#
C++
Java
Python

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

Erlang

Java

Triggers

yes, Notifications (with Streaming only)

yes

pre-commit hooks and post-commit hooks

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

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)

selectable replication factor

Multi-source replication
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

Immediate Consistency

Tunable consistency, set CAP knob accordingly

Eventual Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

links between datasets can be stored

FOREIGN KEY constraints are not supported

Transaction concepts

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

Atomic single-document operations

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

yes, implements WAL (Write ahead log) as well

yes

Snapshots and command logging

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

User concepts

Access control

Access rights for users and roles

yes (enterprise version only)

Users and roles with access to stored procedures

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More resources

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