DBMS > Amazon Redshift vs. AntDB vs. QuestDB

System Properties Comparison Amazon Redshift vs. AntDB vs. QuestDB

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

A scalable, multi-tenant, MPP-architectured RDBMS for OLTP and OLAP operations, highly compatible with Oracle

A high performance open source SQL database for time series data

Primary database model

Relational DBMS

Time Series DBMS

Secondary database models

Relational DBMS

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Trend Chart

Score	15.25
Rank	#38	Overall
	#23	Relational DBMS

Score	0.09
Rank	#342	Overall
	#149	Relational DBMS

Score	2.81
Rank	#98	Overall
	#7	Time Series DBMS

Website

aws.amazon.com/redshift

www.asiainfo.com/en_us/product_aisware_antdb_detail.html

questdb.io

Technical documentation

docs.aws.amazon.com/redshift

questdb.io/docs

Developer

Amazon (based on PostgreSQL)

AsiaInfo Technologies Limited

QuestDB Technology Inc

Initial release

2012

2014

License

Commercial or Open Source

commercial

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

Java (Zero-GC), C++, Rust

Server operating systems

hosted

Linux
macOS
Windows

Data scheme

yes

schema-free via InfluxDB Line Protocol

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

SQL2016 compliant

SQL with time-series extensions

APIs and other access methods

JDBC
ODBC

JDBC
MySQL protocol compliant
ODBC

HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol

Supported programming languages

All languages supporting JDBC/ODBC

PostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust

over HTTP

Server-side scripts

Stored procedures

user defined functions

in Python

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by timestamps)

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication with eventual consistency

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

yes

Transaction concepts

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

ACID

ACID for single-table writes

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

through memory mapped files

User concepts

Access control

fine grained access rights according to SQL-standard

More information provided by the system vendor

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