DBMS > AgensGraph vs. Amazon Redshift vs. Blueflood vs. Heroic

System Properties Comparison AgensGraph vs. Amazon Redshift vs. Blueflood vs. Heroic

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Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

Large scale data warehouse service for use with business intelligence tools

Scalable TimeSeries DBMS based on Cassandra

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Primary database model

Graph DBMS
Relational DBMS

Relational DBMS

Time Series DBMS

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

Score	0.23
Rank	#315	Overall
	#26	Graph DBMS
	#140	Relational DBMS

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	0.13
Rank	#346	Overall
	#33	Time Series DBMS

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Website

bitnine.net/agensgraph

aws.amazon.com/redshift

blueflood.io

github.com/spotify/heroic

Technical documentation

bitnine.net/documentation

docs.aws.amazon.com/redshift

github.com/rax-maas/blueflood/wiki

spotify.github.io/heroic

Developer

Bitnine Global Inc.

Amazon (based on PostgreSQL)

Rackspace

Spotify

Initial release

2016

2012

2013

2014

Current release

2.1, December 2018

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

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

Server operating systems

Linux
OS X
Windows

hosted

Linux
OS X

Data scheme

depending on used data model

yes

predefined scheme

schema-free

Typing

predefined data types such as float or date

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

yes

restricted

yes

via Elasticsearch

SQL

Support of SQL

yes

does not fully support an SQL-standard

APIs and other access methods

Cypher Query Language
JDBC

JDBC
ODBC

HTTP REST

HQL (Heroic Query Language, a JSON-based language)
HTTP API

Supported programming languages

C
Java
JavaScript
Python

All languages supporting JDBC/ODBC

Server-side scripts

Stored procedures

yes

user defined functions

in Python

Triggers

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

based on Cassandra

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

selectable replication factor

based on Cassandra

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

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 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

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