DBMS > Amazon Redshift vs. JaguarDB vs. Sadas Engine vs. TigerGraph

System Properties Comparison Amazon Redshift vs. JaguarDB vs. Sadas Engine vs. TigerGraph

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Performant, highly scalable DBMS for AI and IoT applications

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Relational DBMS

Key-value store
Vector DBMS

Relational DBMS

Graph DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	0.06
Rank	#381	Overall
	#59	Key-value stores
	#14	Vector DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Website

aws.amazon.com/redshift

www.jaguardb.com

www.sadasengine.com

www.tigergraph.com

Technical documentation

docs.aws.amazon.com/redshift

www.jaguardb.com/support.html

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

docs.tigergraph.com

Developer

Amazon (based on PostgreSQL)

DataJaguar, Inc.

SADAS s.r.l.

Initial release

2012

2015

2006

2017

Current release

3.3 July 2023

8.0

License

Commercial or Open Source

commercial

Open Source

GPL V3.0

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++

the server part. Clients available in other languages

C++

Server operating systems

hosted

Linux

AIX
Linux
Windows

Linux

Data scheme

yes

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

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

SQL-like query language (GSQL)

APIs and other access methods

JDBC
ODBC

JDBC
ODBC
Proprietary protocol

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

All languages supporting JDBC/ODBC

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

.Net
C
C#
C++
Groovy
Java
PHP
Python

C++
Java

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate 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

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

managed by 'Learn by Usage'

User concepts

Access control

fine grained access rights according to SQL-standard

rights management via user accounts

Access rights for users, groups and roles according to SQL-standard

Role-based access control

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