DBMS > Amazon DynamoDB vs. BigchainDB vs. FoundationDB vs. SAP SQL Anywhere vs. TimesTen

System Properties Comparison Amazon DynamoDB vs. BigchainDB vs. FoundationDB vs. SAP SQL Anywhere vs. TimesTen

Editorial information provided by DB-Engines

Name

Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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

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

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

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

In-Memory RDBMS compatible to Oracle

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

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

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.85
Rank	#208	Overall
	#35	Document stores

Score	1.06
Rank	#185	Overall
	#31	Document stores
	#28	Key-value stores
	#85	Relational DBMS

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Website

aws.amazon.com/dynamodb

www.bigchaindb.com

github.com/apple/foundationdb

www.sap.com/products/technology-platform/sql-anywhere.html

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

Technical documentation

docs.aws.amazon.com/dynamodb

bigchaindb.readthedocs.io/en/latest

apple.github.io/foundationdb

help.sap.com/docs/SAP_SQL_Anywhere

docs.oracle.com/database/timesten-18.1

Developer

Amazon

FoundationDB

SAP

formerly Sybase

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2012

2016

2013

1992

1998

Current release

6.2.28, November 2020

17, July 2015

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

AGPL v3

Open Source

Apache 2.0

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

Python

C++

Server operating systems

hosted

Linux

Linux
OS X
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

schema-free

some layers support schemas

yes

Typing

predefined data types such as float or date

yes

some layers support typing

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

supported in specific SQL layer only

yes

APIs and other access methods

RESTful HTTP API

CLI Client
RESTful HTTP API

ADO.NET
HTTP API
JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Go
Haskell
Java
JavaScript
Python
Ruby

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

in SQL-layer only

yes, in C/C++, Java, .Net or Perl

PL/SQL

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

yes

Source-replica replication

Database mirroring

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

Linearizable consistency

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

in SQL-layer only

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes,with MongoDB ord RethinkDB

yes

by means of logfiles and checkpoints

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

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