DBMS > NuoDB vs. Snowflake vs. Spark SQL vs. STSdb

System Properties Comparison NuoDB vs. Snowflake vs. Spark SQL vs. STSdb

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Editorial information provided by DB-Engines

Name

Description

NuoDB is a webscale distributed database that supports SQL and ACID transactions

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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Relational DBMS

Key-value store

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

Score	0.94
Rank	#197	Overall
	#92	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Website

www.3ds.com/nuodb-distributed-sql-database

www.snowflake.com

spark.apache.org/sql

github.com/STSSoft/STSdb4

Technical documentation

doc.nuodb.com

docs.snowflake.net/manuals/index.html

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

Developer

Dassault Systèmes

originally NuoDB, Inc.

Snowflake Computing Inc.

Apache Software Foundation

STS Soft SC

Initial release

2013

2014

2011

Current release

3.5.0 ( 2.13), September 2023

4.0.8, September 2015

License

Commercial or Open Source

commercial

limited edition free

commercial

Open Source

Apache 2.0

Open Source

GPLv2, commercial license 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

C++

Scala

Server operating systems

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

hosted

Linux
OS X
Windows

Windows

Data scheme

yes

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

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

ADO.NET
JDBC
ODBC

CLI Client
JDBC
ODBC

JDBC
ODBC

.NET Client API

Supported programming languages

.Net
C
C++
Go
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby

JavaScript (Node.js)
Python

Java
Python
R
Scala

C#
Java

Server-side scripts

Stored procedures

Java, SQL

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

data is dynamically stored/cached on the nodes where it is read/written

yes

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Managed transparently by NuoDB

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

tunable commit protocol

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

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

Temporary table

User concepts

Access control

Standard SQL roles/ privileges, Administrative Users

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

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