DBMS > Amazon Redshift vs. atoti vs. Blazegraph vs. FoundationDB vs. QuestDB

System Properties Comparison Amazon Redshift vs. atoti vs. Blazegraph vs. FoundationDB vs. QuestDB

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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

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.

A high performance open source SQL database for time series data

Primary database model

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	15.25
Rank	#38	Overall
	#23	Relational DBMS

Score	0.45
Rank	#253	Overall
	#13	Object oriented DBMS

Score	0.74
Rank	#217	Overall
	#19	Graph DBMS
	#8	RDF stores

Score	0.97
Rank	#191	Overall
	#32	Document stores
	#28	Key-value stores
	#87	Relational DBMS

Score	2.81
Rank	#98	Overall
	#7	Time Series DBMS

Website

aws.amazon.com/redshift

atoti.io

blazegraph.com

github.com/apple/foundationdb

questdb.io

Technical documentation

docs.aws.amazon.com/redshift

docs.atoti.io

wiki.blazegraph.com

apple.github.io/foundationdb

questdb.io/docs

Developer

Amazon (based on PostgreSQL)

ActiveViam

Blazegraph

FoundationDB

QuestDB Technology Inc

Initial release

2012

2006

2013

2014

Current release

2.1.5, March 2019

6.2.28, November 2020

License

Commercial or Open Source

commercial

free versions available

Open Source

extended commercial license available

Open Source

Apache 2.0

Open Source

Apache 2.0

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

Java

C++

Java (Zero-GC), C++, Rust

Server operating systems

hosted

Linux
OS X
Windows

Linux
macOS
Windows

Data scheme

yes

schema-free

some layers support schemas

yes

schema-free via InfluxDB Line Protocol

Typing

predefined data types such as float or date

yes

RDF literal types

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

Multidimensional Expressions (MDX)

SPARQL is used as query language

supported in specific SQL layer only

SQL with time-series extensions

APIs and other access methods

JDBC
ODBC

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol

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

PostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust

over HTTP

Server-side scripts

Stored procedures

user defined functions

in Python

Python

yes

in SQL-layer only

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

Sharding

horizontal partitioning (by timestamps)

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication with eventual consistency

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Linearizable consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Relationships in Graphs

in SQL-layer only

Transaction concepts

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

ACID

ACID for single-table writes

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

through memory mapped files

User concepts

Access control

fine grained access rights according to SQL-standard

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

More information provided by the system vendor

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