DBMS > Sadas Engine vs. Splice Machine vs. SWC-DB vs. YTsaurus

System Properties Comparison Sadas Engine vs. Splice Machine vs. SWC-DB vs. YTsaurus

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Editorial information provided by DB-Engines

Name

Description

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

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

A high performance, scalable Wide Column DBMS

YTsaurus is an open source platform for distributed storage and processing.

Primary database model

Relational DBMS

Wide column store

Document store
Key-value store

Secondary database models

Time Series DBMS

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

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Score	0.21
Rank	#324	Overall
	#45	Document stores
	#48	Key-value stores

Website

www.sadasengine.com

splicemachine.com

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

ytsaurus.tech

Technical documentation

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

splicemachine.com/how-it-works

ytsaurus.tech/docs/en

Developer

SADAS s.r.l.

Splice Machine

Alex Kashirin

Yandex

Initial release

2006

2014

2020

2023

Current release

8.0

3.1, March 2021

0.5, April 2021

License

Commercial or Open Source

commercial

free trial version available

Open Source

AGPL 3.0, commercial license available

Open Source

GPL V3

Open Source

Apache License, Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Java

C++

Server operating systems

AIX
Linux
Windows

Linux
OS X
Solaris
Windows

Linux

Ubuntu

Data scheme

yes

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

YQL, an SQL-based language, is supported

APIs and other access methods

JDBC
ODBC
Proprietary protocol

JDBC
Native Spark Datasource
ODBC

Proprietary protocol
Thrift

Supported programming languages

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

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

C++

C++
Go
Java
JavaScript
Python

Server-side scripts

Stored procedures

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Shared Nothhing Auto-Sharding, Columnar Partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

yes

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

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (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

managed by 'Learn by Usage'

yes

User concepts

Access control

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

Access Control Lists

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