DBMS > Amazon Redshift vs. Apache Doris vs. Graph Engine vs. TigerGraph

System Properties Comparison Amazon Redshift vs. Apache Doris vs. Graph 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

An MPP-based analytics DBMS embracing the MySQL protocol

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

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

Primary database model

Relational DBMS

Graph DBMS
Key-value store

Graph DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	0.60
Rank	#247	Overall
	#113	Relational DBMS

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Website

aws.amazon.com/redshift

doris.apache.org
github.com/apache/doris

www.graphengine.io

www.tigergraph.com

Technical documentation

docs.aws.amazon.com/redshift

github.com/apache/doris/wiki

www.graphengine.io/docs/manual

docs.tigergraph.com

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation, originally contributed from Baidu

Microsoft

Initial release

2012

2017

2010

2017

Current release

1.2.2, February 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

MIT License

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

.NET and C

C++

Server operating systems

hosted

Linux

.NET

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

yes

SQL-like query language (GSQL)

APIs and other access methods

JDBC
ODBC

JDBC
MySQL client

RESTful HTTP API

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

Supported programming languages

All languages supporting JDBC/ODBC

Java

C#
C++
F#
Visual Basic

C++
Java

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

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

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

Role-based access control

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