DBMS > Amazon Redshift vs. Datomic vs. Dgraph vs. VelocityDB

System Properties Comparison Amazon Redshift vs. Datomic vs. Dgraph vs. VelocityDB

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Distributed and scalable native Graph DBMS

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Relational DBMS

Graph DBMS

Graph DBMS
Object oriented DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	1.53
Rank	#152	Overall
	#15	Graph DBMS

Score	0.11
Rank	#354	Overall
	#37	Graph DBMS
	#16	Object oriented DBMS

Website

aws.amazon.com/redshift

www.datomic.com

dgraph.io

velocitydb.com

Technical documentation

docs.aws.amazon.com/redshift

docs.datomic.com

dgraph.io/docs

velocitydb.com/UserGuide

Developer

Amazon (based on PostgreSQL)

Cognitect

Dgraph Labs, Inc.

VelocityDB Inc

Initial release

2012

2016

2011

Current release

1.0.7075, December 2023

7.x

License

Commercial or Open Source

commercial

limited edition free

Open Source

Apache 2.0

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

Java, Clojure

Server operating systems

hosted

All OS with a Java VM

Linux
OS X
Windows

Any that supports .NET

Data scheme

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

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

.Net

Supported programming languages

All languages supporting JDBC/ODBC

Clojure
Java

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

.Net

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Transaction Functions

Triggers

By using transaction functions

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

But extensive use of caching in the application peers

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

But extensive use of caching in the application peers

Synchronous replication via Raft

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

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

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Planned for future releases

Based on Windows Authentication

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