DBMS > Amazon Redshift vs. Blazegraph vs. Cachelot.io vs. HEAVY.AI vs. PouchDB

System Properties Comparison Amazon Redshift vs. Blazegraph vs. Cachelot.io vs. HEAVY.AI vs. PouchDB

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.

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.

In-memory caching system

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Secondary database models

Spatial DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	0.81
Rank	#213	Overall
	#19	Graph DBMS
	#8	RDF stores

Score	0.04
Rank	#388	Overall
	#62	Key-value stores

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Website

aws.amazon.com/redshift

blazegraph.com

cachelot.io

github.com/heavyai/heavydb
www.heavy.ai

pouchdb.com

Technical documentation

docs.aws.amazon.com/redshift

wiki.blazegraph.com

docs.heavy.ai

pouchdb.com/guides

Developer

Amazon (based on PostgreSQL)

Blazegraph

HEAVY.AI, Inc.

Apache Software Foundation

Initial release

2012

2006

2015

2016

2012

Current release

2.1.5, March 2019

5.10, January 2022

7.1.1, June 2019

License

Commercial or Open Source

commercial

Open Source

extended commercial license available

Open Source

Simplified BSD License

Open Source

Apache Version 2; enterprise edition available

Open Source

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++

C++ and CUDA

JavaScript

Server operating systems

hosted

Linux
OS X
Windows

FreeBSD
Linux
OS X

Linux

server-less, requires a JavaScript environment (browser, Node.js)

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

RDF literal types

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

via views

SQL

Support of SQL

yes

does not fully support an SQL-standard

SPARQL is used as query language

yes

APIs and other access methods

JDBC
ODBC

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

Memcached protocol

JDBC
ODBC
Thrift
Vega

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

All languages supporting JDBC/ODBC/Thrift
Python

JavaScript

Server-side scripts

Stored procedures

user defined functions

in Python

yes

View functions in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Round robin

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

none

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Relationships in Graphs

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

by using IndexedDB, WebSQL or LevelDB as backend

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)

fine grained access rights according to SQL-standard

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