DBMS > Newts vs. Riak KV vs. Riak TS vs. Sadas Engine vs. Snowflake

System Properties Comparison Newts vs. Riak KV vs. Riak TS vs. Sadas Engine vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

Time Series DBMS based on Cassandra

Distributed, fault tolerant key-value store

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

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

Time Series DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Time Series DBMS

Relational DBMS

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

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

opennms.github.io/newts

www.sadasengine.com

www.snowflake.com

Technical documentation

github.com/OpenNMS/newts/wiki

www.tiot.jp/riak-docs/riak/kv/latest

www.tiot.jp/riak-docs/riak/ts/latest

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

docs.snowflake.net/manuals/index.html

Developer

OpenNMS Group

OpenSource, formerly Basho Technologies

Open Source, formerly Basho Technologies

SADAS s.r.l.

Snowflake Computing Inc.

Initial release

2014

2009

2015

2006

2014

Current release

3.2.0, December 2022

3.0.0, September 2022

8.0

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache version 2, commercial enterprise edition

Open Source

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

Erlang

C++

Server operating systems

Linux
OS X
Windows

Linux
OS X

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

restricted

yes

SQL

Support of SQL

yes, limited

yes

APIs and other access methods

HTTP REST
Java API

HTTP API
Native Erlang Interface

JDBC
ODBC
Proprietary protocol

CLI Client
JDBC
ODBC

Supported programming languages

Java

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Erlang

user defined functions

Triggers

yes

pre-commit hooks and post-commit hooks

yes

pre-commit hooks and post-commit hooks

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

no "single point of failure"

Sharding

horizontal partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

selectable replication factor

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

links between data sets can be stored

links between datasets can be stored

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

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'

User concepts

Access control

yes, using Riak Security

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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