DBMS > Amazon DynamoDB vs. BigchainDB vs. IBM Db2 vs. MySQL vs. YottaDB

System Properties Comparison Amazon DynamoDB vs. BigchainDB vs. IBM Db2 vs. MySQL vs. YottaDB

Editorial information provided by DB-Engines

Name

Description

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

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

Common in IBM host environments, 2 different versions for host and Windows/Linux

Widely used open source RDBMS

A fast and solid embedded Key-value store

Primary database model

Document store
Key-value store

Document store

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Relational DBMS

Key/Value like access via memcached API

Key-value store

Secondary database models

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

Document store
Spatial DBMS

Relational DBMS

using the Octo plugin

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

Score	71.85
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.76
Rank	#215	Overall
	#36	Document stores

Score	122.77
Rank	#9	Overall
	#6	Relational DBMS

Score	1022.76
Rank	#2	Overall
	#2	Relational DBMS

Score	0.18
Rank	#316	Overall
	#47	Key-value stores

Website

aws.amazon.com/dynamodb

www.bigchaindb.com

www.ibm.com/products/db2

www.mysql.com

yottadb.com

Technical documentation

docs.aws.amazon.com/dynamodb

bigchaindb.readthedocs.io/en/latest

www.ibm.com/docs/en/db2

dev.mysql.com/doc

yottadb.com/resources/documentation

Developer

Amazon

IBM

Oracle

since 2010, originally MySQL AB, then Sun

YottaDB, LLC

Initial release

2012

2016

1983

host version

1995

2001

Current release

12.1, October 2016

9.0.0, July 2024

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

AGPL v3

commercial

free version is available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

AGPL 3.0

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

Python

C and C++

Server operating systems

hosted

Linux

AIX
HP-UX
Linux
Solaris
Windows
z/OS

FreeBSD
Linux
OS X
Solaris
Windows

Docker
Linux

Data scheme

schema-free

yes

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

by using the Octo plugin

APIs and other access methods

RESTful HTTP API

CLI Client
RESTful HTTP API

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

ADO.NET
JDBC
ODBC
Proprietary native API

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Go
Haskell
Java
JavaScript
Python
Ruby

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

yes

proprietary syntax

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

only with Windows/Unix/Linux Version

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

yes

with separate tools (MQ, InfoSphere)

Multi-source replication
Source-replica replication

yes

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

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

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

not for MyISAM storage engine

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

yes,with MongoDB ord RethinkDB

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

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

yes

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

Users and groups based on OS-security mechanisms

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