DBMS > Amazon DynamoDB vs. Atos Standard Common Repository vs. FoundationDB vs. HEAVY.AI vs. OrigoDB

System Properties Comparison Amazon DynamoDB vs. Atos Standard Common Repository vs. FoundationDB vs. HEAVY.AI vs. OrigoDB

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.

Description

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

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

Ordered key-value store. Core features are complimented by layers.

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

A fully ACID in-memory object graph database

Primary database model

Document store
Key-value store

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Relational DBMS

Document store
Object oriented DBMS

Secondary database models

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	1.03
Rank	#190	Overall
	#31	Document stores
	#28	Key-value stores
	#89	Relational DBMS

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Website

aws.amazon.com/dynamodb

atos.net/en/convergence-creators/portfolio/standard-common-repository

github.com/apple/foundationdb

github.com/heavyai/heavydb
www.heavy.ai

origodb.com

Technical documentation

docs.aws.amazon.com/dynamodb

apple.github.io/foundationdb

docs.heavy.ai

origodb.com/docs

Developer

Amazon

Atos Convergence Creators

FoundationDB

HEAVY.AI, Inc.

Robert Friberg et al

Initial release

2012

2016

2013

2016

2009

under the name LiveDB

Current release

1703

6.2.28, November 2020

5.10, January 2022

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Open Source

Apache 2.0

Open Source

Apache Version 2; enterprise edition available

Open Source

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

Java

C++

C++ and CUDA

Server operating systems

hosted

Linux

Linux
OS X
Windows

Linux

Linux
Windows

Data scheme

schema-free

Schema and schema-less with LDAP views

schema-free

some layers support schemas

yes

Typing

predefined data types such as float or date

yes

optional

some layers support typing

yes

User defined using .NET types and collections

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

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

supported in specific SQL layer only

yes

APIs and other access methods

RESTful HTTP API

LDAP

JDBC
ODBC
Thrift
Vega

.NET Client API
HTTP API
LINQ

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

All languages with LDAP bindings

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

All languages supporting JDBC/ODBC/Thrift
Python

.Net

Server-side scripts

Stored procedures

in SQL-layer only

yes

Triggers

yes

by integration with AWS Lambda

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

Round robin

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency or Eventual Consistency depending on configuration

Linearizable consistency

Immediate Consistency

Foreign keys

Referential integrity

in SQL-layer only

depending on model

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

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

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)

LDAP bind authentication

fine grained access rights according to SQL-standard

Role based authorization

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