DBMS > Amazon Redshift vs. Drizzle vs. FatDB vs. TimescaleDB vs. Transwarp KunDB

System Properties Comparison Amazon Redshift vs. Drizzle vs. FatDB vs. TimescaleDB vs. Transwarp KunDB

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.

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

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.

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

OLTP DBMS based on a distributed architecture and highly compatible with MySQL and Oracle

Primary database model

Relational DBMS

Document store
Key-value store

Time Series DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	15.25
Rank	#38	Overall
	#23	Relational DBMS

Score	4.06
Rank	#73	Overall
	#5	Time Series DBMS

Score	0.04
Rank	#362	Overall
	#154	Relational DBMS

Website

aws.amazon.com/redshift

www.timescale.com

www.transwarp.cn/en/product/kundb

Technical documentation

docs.aws.amazon.com/redshift

docs.timescale.com

Developer

Amazon (based on PostgreSQL)

Drizzle project, originally started by Brian Aker

FatCloud

Timescale

Transwarp

Initial release

2012

2008

2012

2017

Current release

7.2.4, September 2012

2.15.0, May 2024

License

Commercial or Open Source

commercial

Open Source

GNU GPL

commercial

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

C++

Server operating systems

hosted

FreeBSD
Linux
OS X

Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

with proprietary extensions

Via inetgration in SQL Server

yes

full PostgreSQL SQL syntax

yes

APIs and other access methods

JDBC
ODBC

JDBC

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

All languages supporting JDBC/ODBC

C
C++
Java
PHP

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions

in Python

yes

via applications

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

yes

Triggers

hooks for callbacks inside the server can be used.

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes, across time and space (hash partitioning) attributes

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

selectable replication factor

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

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

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

Can implement custom security layer via applications

fine grained access rights according to SQL-standard

yes

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