DBMS > FoundationDB vs. Microsoft Azure Synapse Analytics vs. OpenQM vs. SQLite vs. Teradata Aster

System Properties Comparison FoundationDB vs. Microsoft Azure Synapse Analytics vs. OpenQM vs. SQLite vs. Teradata Aster

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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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

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

QpenQM is a high-performance, self-tuning, multi-value DBMS

Widely used embeddable, in-process RDBMS

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

Relational DBMS

Multivalue DBMS

Relational 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	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	0.34
Rank	#284	Overall
	#10	Multivalue DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

github.com/apple/foundationdb

azure.microsoft.com/services/synapse-analytics

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

www.sqlite.org

Technical documentation

apple.github.io/foundationdb

docs.microsoft.com/azure/synapse-analytics

www.sqlite.org/docs.html

Developer

FoundationDB

Microsoft

Rocket Software, originally Martin Phillips

Dwayne Richard Hipp

Teradata

Initial release

2013

2016

1993

2000

2005

Current release

6.2.28, November 2020

3.4-12

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

GPLv2, extended commercial license available

Open Source

Public Domain

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

C++

Server operating systems

Linux
OS X
Windows

hosted

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

server-less

Linux

Data scheme

schema-free

some layers support schemas

yes

with some exceptions

yes

dynamic column types

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

not rigid because of 'dynamic typing' concept.

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

yes

SQL

Support of SQL

supported in specific SQL layer only

yes

SQL-92 is not fully supported

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

C#
Java
PHP

.Net
Basic
C
Java
Objective C
PHP
Python

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

in SQL-layer only

Transact SQL

yes

R packages

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

yes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

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

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

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

via file-system locks

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.

yes

User concepts

Access control

yes

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

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