DBMS > Apache Drill vs. HyperSQL vs. Sadas Engine vs. Snowflake

System Properties Comparison Apache Drill vs. HyperSQL vs. Sadas Engine vs. Snowflake

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Editorial information provided by DB-Engines

Name

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

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

Primary database model

Document store
Relational DBMS

Relational DBMS

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

Score	2.02
Rank	#124	Overall
	#22	Document stores
	#59	Relational DBMS

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

Technical documentation

drill.apache.org/docs

hsqldb.org/web/hsqlDocsFrame.html

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation

SADAS s.r.l.

Snowflake Computing Inc.

Initial release

2012

2001

2006

2014

Current release

1.20.3, January 2023

2.7.2, June 2023

8.0

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

based on BSD license

commercial

free trial version available

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

Java

C++

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

AIX
Linux
Windows

hosted

Data scheme

schema-free

yes

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

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

SQL SELECT statement is SQL:2003 compliant

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

HTTP API

JDBC via HTTP
JDBC
ODBC

JDBC
ODBC
Proprietary protocol

CLI Client
JDBC
ODBC

Supported programming languages

C++

All languages supporting JDBC/ODBC
Java

.Net
C
C#
C++
Groovy
Java
PHP
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

Java, SQL

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

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

Depending on the underlying data source

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

Depending on the underlying data source

yes

managed by 'Learn by Usage'

User concepts

Access control

Depending on the underlying data source

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

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

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