DBMS > ClickHouse vs. NSDb vs. Teradata Aster

System Properties Comparison ClickHouse vs. NSDb vs. Teradata Aster

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Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Platform for big data analytics on multistructured data sources and types

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Time Series DBMS

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

Score	17.44
Rank	#31	Overall
	#19	Relational DBMS

Score	0.00
Rank	#392	Overall
	#44	Time Series DBMS

Website

clickhouse.com

nsdb.io

Technical documentation

clickhouse.com/docs

nsdb.io/Architecture

Developer

Clickhouse Inc.

Teradata

Initial release

2016

2017

2005

Current release

v24.6.2.17-stable, July 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

ClickHouse Cloud: Get the performance you love from open source ClickHouse in a serverless offering that takes care of the details so you can spend more time getting insight out of the fastest database on earth.

Implementation language

C++

Java, Scala

Server operating systems

FreeBSD
Linux
macOS

Linux
macOS

Linux

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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

in Aster File Store

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

SQL-like query language

yes

APIs and other access methods

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

gRPC
HTTP REST
WebSocket

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Rust
Scala

3rd party library

Java
Scala

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

yes

R packages

Triggers

Partitioning methods

Methods for storing different data on different nodes

key based and custom

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

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 Apache Lucene

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

Access rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

fine grained access rights according to SQL-standard

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More resources

Recent citations in the news

ClickHouse Announces Strategic Collaboration Agreement with AWS to Advance Real-Time Data Analytics and Generative AI Innovation
10 December 2024, Business Wire

A Beginner’s Guide to ClickHouse Database
13 September 2024, KDnuggets

Azur Games migrates all game analytics data to ClickHouse Cloud on AWS
16 July 2024, AWS Blog

Database startup ClickHouse Announces PeerDB Acquistion
31 July 2024, Tech Times

Real-time database startup ClickHouse acquires PeerDB to expand its Postgres support
30 July 2024, TechCrunch

provided by Google News

Northwestern Analytics Partners with Teradata Aster to Host Hackathon
23 May 2014, Northwestern Engineering

Teradata Aster gets graph database, HDFS-compatible file store
8 October 2013, ZDNet

Teradata's Aster shows how the flowers of fraud bloom
23 April 2015, The Register

Teradata Integrates Big Data Analytic Architecture
22 October 2012, PR Newswire

Big Data needs drive R as a powerful enterprise ready language
28 July 2014, SiliconANGLE News

provided by Google News

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