DBMS > Snowflake vs. Teradata Aster vs. Ultipa

System Properties Comparison Snowflake vs. Teradata Aster vs. Ultipa

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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

Cloud-based data warehousing service for structured and semi-structured data

Platform for big data analytics on multistructured data sources and types

High performance Graph DBMS supporting HTAP high availability cluster deployment

Primary database model

Relational DBMS

Graph DBMS

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Trend Chart

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.13
Rank	#335	Overall
	#31	Graph DBMS

Website

www.snowflake.com

www.ultipa.com

Technical documentation

docs.snowflake.net/manuals/index.html

www.ultipa.com/document

Developer

Snowflake Computing Inc.

Teradata

Ultipa

Initial release

2014

2005

2019

License

Commercial or Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Server operating systems

hosted

Linux

Data scheme

yes

support of semi-structured data formats (JSON, XML, Avro)

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

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

SQL

Support of SQL

yes

APIs and other access methods

CLI Client
JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB

RESTful HTTP API

Supported programming languages

JavaScript (Node.js)
Python

C
C#
C++
Java
Python
R

C++
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

R packages

Triggers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

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.

User concepts

Access control

Users with fine-grained authorization concept, user roles and pluggable authentication

fine grained access rights according to SQL-standard

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