DBMS > Amazon Redshift vs. FoundationDB vs. Memcached vs. Microsoft Azure Synapse Analytics vs. TerminusDB

System Properties Comparison Amazon Redshift vs. FoundationDB vs. Memcached vs. Microsoft Azure Synapse Analytics vs. TerminusDB

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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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

Large scale data warehouse service for use with business intelligence tools

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

In-memory key-value store, originally intended for caching

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Relational DBMS

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Key-value store

Relational DBMS

Graph DBMS

Secondary database models

Document store
RDF store

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

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

Score	19.42
Rank	#32	Overall
	#4	Key-value stores

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Website

aws.amazon.com/redshift

github.com/apple/foundationdb

www.memcached.org

azure.microsoft.com/services/synapse-analytics

terminusdb.com

Technical documentation

docs.aws.amazon.com/redshift

apple.github.io/foundationdb

github.com/memcached/memcached/wiki

docs.microsoft.com/azure/synapse-analytics

terminusdb.github.io/terminusdb/#

Developer

Amazon (based on PostgreSQL)

FoundationDB

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Microsoft

DataChemist Ltd.

Initial release

2012

2013

2003

2016

2018

Current release

6.2.28, November 2020

1.6.27, May 2024

11.0.0, January 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

BSD license

commercial

Open Source

GPL V3

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

C++

Prolog, Rust

Server operating systems

hosted

Linux
OS X
Windows

FreeBSD
Linux
OS X
Unix
Windows

hosted

Linux

Data scheme

yes

schema-free

some layers support schemas

schema-free

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.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

supported in specific SQL layer only

yes

SQL-like query language (WOQL)

APIs and other access methods

JDBC
ODBC

Proprietary protocol

ADO.NET
JDBC
ODBC

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

C#
Java
PHP

JavaScript
Python

Server-side scripts

Stored procedures

user defined functions

in Python

in SQL-layer only

Transact SQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding, horizontal partitioning

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Repcached, a Memcached patch, provides this functionallity

yes

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Linearizable consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

in SQL-layer only

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

yes

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 journaling

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes

using SASL (Simple Authentication and Security Layer) protocol

yes

Role-based access control

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