DBMS > Amazon Redshift vs. Blazegraph vs. FoundationDB vs. Google Cloud Datastore vs. mSQL

System Properties Comparison Amazon Redshift vs. Blazegraph vs. FoundationDB vs. Google Cloud Datastore vs. mSQL

Editorial information provided by DB-Engines

Name

Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.

Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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

High-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.

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

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

mSQL (Mini SQL) is a simple and lightweight RDBMS

Primary database model

Relational DBMS

Graph DBMS
RDF store

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Document store

Relational DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.75
Rank	#219	Overall
	#19	Graph DBMS
	#8	RDF stores

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

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Website

aws.amazon.com/redshift

blazegraph.com

github.com/apple/foundationdb

cloud.google.com/datastore

hughestech.com.au/products/msql

Technical documentation

docs.aws.amazon.com/redshift

wiki.blazegraph.com

apple.github.io/foundationdb

cloud.google.com/datastore/docs

Developer

Amazon (based on PostgreSQL)

Blazegraph

FoundationDB

Google

Hughes Technologies

Initial release

2012

2006

2013

2008

1994

Current release

2.1.5, March 2019

6.2.28, November 2020

4.4, October 2021

License

Commercial or Open Source

commercial

Open Source

extended commercial license available

Open Source

Apache 2.0

commercial

free licenses can be provided

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

hosted

Linux
OS X
Windows

hosted

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

Data scheme

yes

schema-free

some layers support schemas

schema-free

yes

Typing

predefined data types such as float or date

yes

RDF literal types

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.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SPARQL is used as query language

supported in specific SQL layer only

SQL-like query language (GQL)

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

APIs and other access methods

JDBC
ODBC

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

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

JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

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

C
C++
Delphi
Java
Perl
PHP
Tcl

Server-side scripts

Stored procedures

user defined functions

in Python

yes

in SQL-layer only

using Google App Engine

Triggers

Callbacks using the Google Apps Engine

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication using Paxos

none

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

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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.

none

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Relationships in Graphs

in SQL-layer only

yes

via ReferenceProperties or Ancestor paths

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

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

fine grained access rights according to SQL-standard

Security and Authentication via Web Application Container (Tomcat, Jetty)

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

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