DBMS > Amazon Redshift vs. Dgraph vs. IBM Db2 vs. Kdb vs. Newts

System Properties Comparison Amazon Redshift vs. Dgraph vs. IBM Db2 vs. Kdb vs. Newts

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Distributed and scalable native Graph DBMS

Common in IBM host environments, 2 different versions for host and Windows/Linux

High performance Time Series DBMS

Time Series DBMS based on Cassandra

Primary database model

Relational DBMS

Graph DBMS

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Time Series DBMS
Vector DBMS

Time Series DBMS

Secondary database models

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

Relational DBMS

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	128.46
Rank	#8	Overall
	#5	Relational DBMS

Score	7.55
Rank	#53	Overall
	#3	Time Series DBMS
	#1	Vector DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

aws.amazon.com/redshift

dgraph.io

www.ibm.com/products/db2

kx.com

opennms.github.io/newts

Technical documentation

docs.aws.amazon.com/redshift

dgraph.io/docs

www.ibm.com/docs/en/db2

code.kx.com

github.com/OpenNMS/newts/wiki

Developer

Amazon (based on PostgreSQL)

Dgraph Labs, Inc.

IBM

Kx Systems, a division of First Derivatives plc

OpenNMS Group

Initial release

2012

2016

1983

host version

2000

kdb was released 2000, kdb+ in 2003

2014

Current release

12.1, October 2016

3.6, May 2018

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

free version is available

commercial

free 32-bit version

Open Source

Apache 2.0

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 and C++

Java

Server operating systems

hosted

Linux
OS X
Windows

AIX
HP-UX
Linux
Solaris
Windows
z/OS

Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

schema-free

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.

yes

Secondary indexes

restricted

yes

table attribute 'grouped'

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

SQL-like query language (q)

APIs and other access methods

JDBC
ODBC

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

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

HTTP REST
Java API

Supported programming languages

All languages supporting JDBC/ODBC

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

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala

Java

Server-side scripts

Stored procedures

user defined functions

in Python

yes

user defined functions

Triggers

yes

with views

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

only with Windows/Unix/Linux Version

horizontal partitioning

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous replication via Raft

yes

with separate tools (MQ, InfoSphere)

Source-replica replication

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

similar paradigm used for internal processing

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

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

Planned for future releases

fine grained access rights according to SQL-standard

rights management via user accounts

More information provided by the system vendor

Specific characteristics

Integrated columnar database & programming system for streaming, real time and historical...
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Competitive advantages

provides seamless scalability; runs on industry standard server platforms; is top-ranked...
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Typical application scenarios

tick database streaming sensor data massive intelligence applications oil and gas...
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Key customers

Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
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Market metrics

kdb+ performance and reliability proven by our customers in critical infrastructure...
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Licensing and pricing models

upon request
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