DBMS > Amazon Redshift vs. Dgraph vs. Drizzle vs. IRONdb vs. NuoDB

System Properties Comparison Amazon Redshift vs. Dgraph vs. Drizzle vs. IRONdb vs. NuoDB

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.

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Large scale data warehouse service for use with business intelligence tools

Distributed and scalable native Graph DBMS

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

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

NuoDB is a webscale distributed database that supports SQL and ACID transactions

Primary database model

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	0.89
Rank	#198	Overall
	#92	Relational DBMS

Website

aws.amazon.com/redshift

dgraph.io

www.circonus.com/solutions/time-series-database/

www.3ds.com/nuodb-distributed-sql-database

Technical documentation

docs.aws.amazon.com/redshift

dgraph.io/docs

docs.circonus.com/irondb/category/getting-started

doc.nuodb.com

Developer

Amazon (based on PostgreSQL)

Dgraph Labs, Inc.

Drizzle project, originally started by Brian Aker

Circonus LLC.

Dassault Systèmes

originally NuoDB, Inc.

Initial release

2012

2016

2008

2017

2013

Current release

7.2.4, September 2012

V0.10.20, January 2018

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

GNU GPL

commercial

limited edition free

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++

C and C++

C++

Server operating systems

hosted

Linux
OS X
Windows

FreeBSD
Linux
OS X

Linux

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Data scheme

yes

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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

with proprietary extensions

SQL-like query language (Circonus Analytics Query Language: CAQL)

yes

APIs and other access methods

JDBC
ODBC

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

JDBC

HTTP API

ADO.NET
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

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

C
C++
Java
PHP

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

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

Server-side scripts

Stored procedures

user defined functions

in Python

yes, in Lua

Java, SQL

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

Automatic, metric affinity per node

data is dynamically stored/cached on the nodes where it is read/written

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous replication via Raft

Multi-source replication
Source-replica replication

configurable replication factor, datacenter aware

yes

Managed transparently by NuoDB

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

tunable commit protocol

Concurrency

Support for concurrent manipulation of data

yes

MVCC

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

Temporary table

User concepts

Access control

fine grained access rights according to SQL-standard

Planned for future releases

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Standard SQL roles/ privileges, Administrative Users

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