DBMS > Snowflake vs. Spark SQL vs. TypeDB

System Properties Comparison Snowflake vs. Spark SQL vs. TypeDB

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Editorial information provided by DB-Engines

Name

Description

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

Spark SQL is a component on top of 'Spark Core' for structured data processing

TypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language

Primary database model

Relational DBMS

Graph DBMS
Relational DBMS

Often described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.

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

Score	123.20
Rank	#9	Overall
	#6	Relational DBMS

Score	19.15
Rank	#33	Overall
	#20	Relational DBMS

Score	0.81
Rank	#217	Overall
	#19	Graph DBMS
	#99	Relational DBMS

Website

www.snowflake.com

spark.apache.org/sql

typedb.com

Technical documentation

docs.snowflake.net/manuals/index.html

spark.apache.org/docs/latest/sql-programming-guide.html

typedb.com/docs

Developer

Snowflake Computing Inc.

Apache Software Foundation

Vaticle

Initial release

2014

2016

Current release

3.5.0 ( 2.13), September 2023

2.26.3, January 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

GPL Version 3, commercial licenses available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Scala

Java

Server operating systems

hosted

Linux
OS X
Windows

Data scheme

yes

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

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

SQL

Support of SQL

yes

SQL-like DML and DDL statements

APIs and other access methods

CLI Client
JDBC
ODBC

JDBC
ODBC

gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)

Supported programming languages

JavaScript (Node.js)
Python

Java
Python
R
Scala

All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala

Server-side scripts

Stored procedures

user defined functions

Triggers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

yes

yes, utilizing Spark Core

Sharding

by using Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Multi-source replication

by using Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

by using Apache Kafka and Apache Zookeeper

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

substituted by the relationship feature

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

yes

at REST API level; other APIs in progress

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Licensing and pricing models

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