DBMS > Newts vs. Riak TS vs. Snowflake vs. SurrealDB vs. Vitess

System Properties Comparison Newts vs. Riak TS vs. Snowflake vs. SurrealDB vs. Vitess

Editorial information provided by DB-Engines

Name

Description

Time Series DBMS based on Cassandra

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

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

A fully ACID transactional, developer-friendly, multi-model DBMS

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Time Series DBMS

Relational DBMS

Document store
Graph DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.86
Rank	#203	Overall
	#34	Document stores
	#18	Graph DBMS

Score	0.82
Rank	#209	Overall
	#97	Relational DBMS

Website

opennms.github.io/newts

www.snowflake.com

surrealdb.com

vitess.io

Technical documentation

github.com/OpenNMS/newts/wiki

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

docs.snowflake.net/manuals/index.html

surrealdb.com/docs

vitess.io/docs

Developer

OpenNMS Group

Open Source, formerly Basho Technologies

Snowflake Computing Inc.

SurrealDB Ltd

The Linux Foundation, PlanetScale

Initial release

2014

2015

2014

2022

2013

Current release

3.0.0, September 2022

v1.5.0, May 2024

15.0.2, December 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

commercial

Open Source

Apache Version 2.0, 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

Java

Erlang

Rust

Server operating systems

Linux
OS X
Windows

Linux
OS X

hosted

Linux
macOS
Windows

Docker
Linux
macOS

Data scheme

schema-free

yes

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

schema-free

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

restricted

yes

SQL

Support of SQL

yes, limited

yes

SQL-like query language

yes

with proprietary extensions

APIs and other access methods

HTTP REST
Java API

HTTP API
Native Erlang Interface

CLI Client
JDBC
ODBC

GraphQL
RESTful HTTP API
WebSocket

ADO.NET
JDBC
MySQL protocol
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

JavaScript (Node.js)
Python

Deno
Go
JavaScript (Node.js)
Rust

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

Erlang

user defined functions

yes

proprietary syntax

Triggers

yes

pre-commit hooks and post-commit hooks

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

selectable replication factor

yes

Multi-source replication
Source-replica replication

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

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

links between datasets can be stored

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

User concepts

Access control

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

yes, based on authentication and database rules

Users with fine-grained authorization concept

no user groups or roles

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