DBMS > FoundationDB vs. Riak TS vs. SWC-DB vs. Teradata Aster

System Properties Comparison FoundationDB vs. Riak TS vs. SWC-DB vs. Teradata Aster

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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

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

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

A high performance, scalable Wide Column DBMS

Platform for big data analytics on multistructured data sources and types

Primary database model

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Time Series DBMS

Wide column store

Relational DBMS

Secondary database models

Time Series DBMS

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

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

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Website

github.com/apple/foundationdb

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

apple.github.io/foundationdb

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

Developer

FoundationDB

Open Source, formerly Basho Technologies

Alex Kashirin

Teradata

Initial release

2013

2015

2020

2005

Current release

6.2.28, November 2020

3.0.0, September 2022

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPL V3

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Erlang

C++

Server operating systems

Linux
OS X
Windows

Linux
OS X

Linux

Data scheme

schema-free

some layers support schemas

schema-free

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

Typing

predefined data types such as float or date

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

in Aster File Store

Secondary indexes

restricted

yes

SQL

Support of SQL

supported in specific SQL layer only

yes, limited

SQL-like query language

yes

APIs and other access methods

HTTP API
Native Erlang Interface

Proprietary protocol
Thrift

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

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
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

in SQL-layer only

Erlang

R packages

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Linearizable consistency

Eventual Consistency

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

in SQL-layer only

links between datasets can be stored

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

User concepts

Access control

fine grained access rights according to SQL-standard

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