DBMS > AgensGraph vs. Amazon Redshift vs. Drizzle vs. RavenDB vs. TigerGraph

System Properties Comparison AgensGraph vs. Amazon Redshift vs. Drizzle vs. RavenDB vs. TigerGraph

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

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

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Open Source Operational and Transactional Enterprise NoSQL Document Database

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

Primary database model

Graph DBMS
Relational DBMS

Relational DBMS

Document store

Graph DBMS

Secondary database models

Graph DBMS
Spatial 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	2.84
Rank	#101	Overall
	#18	Document stores

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Website

bitnine.net/agensgraph

aws.amazon.com/redshift

ravendb.net

www.tigergraph.com

Technical documentation

bitnine.net/documentation

docs.aws.amazon.com/redshift

ravendb.net/docs

docs.tigergraph.com

Developer

Bitnine Global Inc.

Amazon (based on PostgreSQL)

Drizzle project, originally started by Brian Aker

Hibernating Rhinos

Initial release

2016

2012

2008

2010

2017

Current release

2.1, December 2018

7.2.4, September 2012

5.4, July 2022

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Open Source

GNU GPL

Open Source

AGPL version 3, commercial license 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++

Server operating systems

Linux
OS X
Windows

hosted

FreeBSD
Linux
OS X

Linux
macOS
Raspberry Pi
Windows

Linux

Data scheme

depending on used data model

yes

schema-free

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

yes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

with proprietary extensions

SQL-like query language (RQL)

SQL-like query language (GSQL)

APIs and other access methods

Cypher Query Language
JDBC

JDBC
ODBC

JDBC

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

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

Supported programming languages

C
Java
JavaScript
Python

All languages supporting JDBC/ODBC

C
C++
Java
PHP

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C++
Java

Server-side scripts

Stored procedures

yes

user defined functions

in Python

yes

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Multi-source replication
Source-replica replication

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

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

ACID, Cluster-wide transaction available

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Authorization levels configured per client per database

Role-based access control

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