DBMS > Newts vs. ScyllaDB vs. SWC-DB vs. TerminusDB vs. Vitess

System Properties Comparison Newts vs. ScyllaDB vs. SWC-DB vs. TerminusDB vs. Vitess

Editorial information provided by DB-Engines

Name

Description

Time Series DBMS based on Cassandra

Cassandra and DynamoDB compatible wide column store

A high performance, scalable Wide Column DBMS

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Secondary database models

Key-value store

Time Series DBMS

Document store
RDF store

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	4.75
Rank	#68	Overall
	#5	Wide column stores

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Score	0.82
Rank	#209	Overall
	#97	Relational DBMS

Website

opennms.github.io/newts

www.scylladb.com

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

terminusdb.com

vitess.io

Technical documentation

github.com/OpenNMS/newts/wiki

docs.scylladb.com

terminusdb.github.io/terminusdb/#

vitess.io/docs

Developer

OpenNMS Group

ScyllaDB

Alex Kashirin

DataChemist Ltd.

The Linux Foundation, PlanetScale

Initial release

2014

2015

2020

2018

2013

Current release

ScyllaDB Open Source 5.4.1, January 2024

0.5, April 2021

11.0.0, January 2023

15.0.2, December 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Open Source (AGPL), commercial license available

Open Source

GPL V3

Open Source

GPL V3

Open Source

Apache Version 2.0, commercial licenses available

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.

Scylla Cloud: Create real-time applications that run at global scale with Scylla Cloud, the industry’s most powerful NoSQL DBaaS

Implementation language

Java

C++

Prolog, Rust

Server operating systems

Linux
OS X
Windows

Linux

Docker
Linux
macOS

Data scheme

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.

Secondary indexes

yes

cluster global secondary indices

yes

SQL

Support of SQL

SQL-like DML and DDL statements (CQL)

SQL-like query language

SQL-like query language (WOQL)

yes

with proprietary extensions

APIs and other access methods

HTTP REST
Java API

Proprietary protocol (CQL)

compatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift

Proprietary protocol
Thrift

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

Java

For CQL interface: C#, C++, Clojure, Erlang, Go, Haskell, Java, JavaScript, Node.js, Perl, PHP, Python, Ruby, Rust, Scala
For DynamoDB interface: .Net, ColdFusion, Erlang, Groovy, Java, JavaScript, Perl, PHP, Python, Ruby

C++

JavaScript
Python

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

yes, Lua

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

Graph Partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

selectable replication factor

Representation of geographical distribution of servers is possible

Journaling Streams

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency
Tunable Consistency

can be individually decided for each write operation

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

Atomicity and isolation are supported for single operations

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 journaling

yes

In-memory capabilities

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

yes

in-memory tables

yes

User concepts

Access control

Access rights for users can be defined per object

Role-based access control

Users with fine-grained authorization concept

no user groups or roles

More information provided by the system vendor

Specific characteristics

ScyllaDB is engineered to deliver predictable performance at scale. It’s adopted...
» more

Competitive advantages

Highly-performant (efficiently utilizes full resources of a node and network; millions...
» more

Typical application scenarios

ScyllaDB is ideal for applications that require high throughput and low latency at...
» more

Key customers

Discord, Epic Games, Expedia, Zillow, Comcast, Disney+ Hotstar, Samsung, ShareChat,...
» more

Market metrics

ScyllaDB typically offers ~75% total cost of ownership savings, with ~5X higher throughput...
» more

Licensing and pricing models

ScyllaDB Open Source - free open source software (AGPL) ScyllaDB Enterprise - subscription-based...
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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