DBMS > FoundationDB vs. Google Cloud Datastore vs. Microsoft Azure Synapse Analytics vs. OpenQM vs. Stardog

System Properties Comparison FoundationDB vs. Google Cloud Datastore vs. Microsoft Azure Synapse Analytics vs. OpenQM vs. Stardog

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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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

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

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

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

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

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

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	4.36
Rank	#72	Overall
	#12	Document stores

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	0.34
Rank	#284	Overall
	#10	Multivalue DBMS

Score	2.07
Rank	#122	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

github.com/apple/foundationdb

cloud.google.com/datastore

azure.microsoft.com/services/synapse-analytics

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

www.stardog.com

Technical documentation

apple.github.io/foundationdb

cloud.google.com/datastore/docs

docs.microsoft.com/azure/synapse-analytics

docs.stardog.com

Developer

FoundationDB

Google

Microsoft

Rocket Software, originally Martin Phillips

Stardog-Union

Initial release

2013

2008

2016

1993

2010

Current release

6.2.28, November 2020

3.4-12

7.3.0, May 2020

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

GPLv2, extended commercial license available

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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++

Java

Server operating systems

Linux
OS X
Windows

hosted

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux
macOS
Windows

Data scheme

schema-free

some layers support schemas

schema-free

yes

with some exceptions

schema-free and OWL/RDFS-schema support

Typing

predefined data types such as float or date

some layers support typing

yes, details here

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

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

supported in specific SQL layer only

SQL-like query language (GQL)

yes

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C#
Java
PHP

.Net
Basic
C
Java
Objective C
PHP
Python

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

in SQL-layer only

using Google App Engine

Transact SQL

yes

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

Callbacks using the Google Apps Engine

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication using Paxos

yes

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Linearizable consistency

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Immediate Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

in SQL-layer only

yes

via ReferenceProperties or Ancestor paths

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

yes

relationships in graphs

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

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.

yes

User concepts

Access control

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

yes

Access rights can be defined down to the item level

Access rights for users and roles

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