DBMS > Snowflake vs. SwayDB vs. Teradata vs. Vitess

System Properties Comparison Snowflake vs. SwayDB vs. Teradata vs. Vitess

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Editorial information provided by DB-Engines

Name

Description

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

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

A hybrid cloud data analytics software platform (Teradata Vantage)

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

Document store
Spatial DBMS

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

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.04
Rank	#387	Overall
	#61	Key-value stores

Score	44.87
Rank	#22	Overall
	#15	Relational DBMS

Score	0.88
Rank	#203	Overall
	#95	Relational DBMS

Website

Technical documentation

docs.snowflake.net/manuals/index.html

docs.teradata.com

vitess.io/docs

Developer

Snowflake Computing Inc.

Simer Plaha

Teradata

The Linux Foundation, PlanetScale

Initial release

2014

2018

1984

2013

Current release

Teradata Vantage 1.0 MU2, January 2019

15.0.2, December 2022

License

Commercial or Open Source

commercial

Open Source

GNU Affero GPL V3.0

commercial

Open Source

Apache Version 2.0, commercial licenses available

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

Scala

Server operating systems

hosted

hosted
Linux

Docker
Linux
macOS

Data scheme

yes

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

schema-free

yes

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

Secondary indexes

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

yes

SQL

Support of SQL

yes

SQL 2016 + extensions

yes

with proprietary extensions

APIs and other access methods

CLI Client
JDBC
ODBC

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

JavaScript (Node.js)
Python

Java
Kotlin
Scala

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions

yes

UDFs, stored procedures, table functions in parallel

yes

proprietary syntax

Triggers

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

yes

none

Sharding

Hashing

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

Atomic execution of operations

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

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

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

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