DBMS > HEAVY.AI vs. Snowflake vs. SWC-DB vs. Teradata Aster

System Properties Comparison HEAVY.AI vs. Snowflake vs. SWC-DB 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 RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

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

A high performance, scalable Wide Column DBMS

Platform for big data analytics on multistructured data sources and types

Primary database model

Relational DBMS

Wide column store

Relational DBMS

Secondary database models

Spatial DBMS

Time Series DBMS

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

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Website

github.com/heavyai/heavydb
www.heavy.ai

www.snowflake.com

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

docs.heavy.ai

docs.snowflake.net/manuals/index.html

Developer

HEAVY.AI, Inc.

Snowflake Computing Inc.

Alex Kashirin

Teradata

Initial release

2016

2014

2020

2005

Current release

5.10, January 2022

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache Version 2; enterprise edition available

commercial

Open Source

GPL V3

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++ and CUDA

C++

Server operating systems

Linux

hosted

Linux

Data scheme

yes

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

schema-free

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

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC
Thrift
Vega

CLI Client
JDBC
ODBC

Proprietary protocol
Thrift

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

JavaScript (Node.js)
Python

C++

C
C#
C++
Java
Python
R

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

Sharding

Round robin

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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

fine grained access rights according to SQL-standard

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