DBMS > Amazon Redshift vs. AnzoGraph DB vs. SQream DB

System Properties Comparison Amazon Redshift vs. AnzoGraph DB vs. SQream DB

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Relational DBMS

Graph DBMS
RDF store

Relational DBMS

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

Score	22.23
Rank	#32	Overall
	#20	Relational DBMS

Score	0.36
Rank	#313	Overall
	#27	Graph DBMS
	#17	RDF stores

Score	0.90
Rank	#232	Overall
	#108	Relational DBMS

Website

aws.amazon.com/redshift

cambridgesemantics.com/anzograph

sqream.com

Technical documentation

docs.aws.amazon.com/redshift

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

docs.sqream.com

Developer

Amazon (based on PostgreSQL)

Cambridge Semantics

SQream Technologies

Initial release

2012

2018

2017

Current release

2.3, January 2021

2022.1.6, December 2022

License

Commercial or Open Source

commercial

free trial version available

commercial

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++, CUDA, Haskell, Java, Scala

Server operating systems

hosted

Linux

Data scheme

yes

Schema-free and OWL/RDFS-schema support

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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

SQL

Support of SQL

yes

does not fully support an SQL-standard

SPARQL and SPARQL* as primary query language. Cypher preview.

yes

APIs and other access methods

JDBC
ODBC

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

.Net
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

C++
Java
Python

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions and aggregates

user defined functions in Python

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic sharding

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication in MPP-Cluster

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in MPP-Cluster

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

not needed 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

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

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

SQream allows companies to get answers from its data and get new business-insights...
» more

Competitive advantages

Scalability when processing bigger datasets. Faster business insights, with more...
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Typical application scenarios

What can you do with 100x faster SQL analytics? Better and more timely decision-making,...
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Key customers

Some of our customers include: LG-U+, AIS , ACL Mobile, Pubmatic, Telkomsel, LG Electronics
» more

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