DBMS > TerminusDB vs. Vitess

System Properties Comparison TerminusDB vs. Vitess

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Editorial information provided by DB-Engines

Name

Description

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

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Graph DBMS

Relational DBMS

Secondary database models

Document store
RDF store

Document store
Spatial DBMS

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Trend Chart

Score	0.17
Rank	#318	Overall
	#28	Graph DBMS

Score	0.88
Rank	#200	Overall
	#92	Relational DBMS

Website

terminusdb.com

vitess.io

Technical documentation

terminusdb.github.io/terminusdb/#

vitess.io/docs

Developer

DataChemist Ltd.

The Linux Foundation, PlanetScale

Initial release

2018

2013

Current release

11.0.0, January 2023

15.0.2, December 2022

License

Commercial or Open Source

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.

Implementation language

Prolog, Rust

Server operating systems

Linux

Docker
Linux
macOS

Data scheme

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

SQL

Support of SQL

SQL-like query language (WOQL)

yes

with proprietary extensions

APIs and other access methods

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

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

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Graph Partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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 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

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

User concepts

Access control

Role-based access control

Users with fine-grained authorization concept

no user groups or roles

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More resources

Recent citations in the news

Trinity College spinout TerminusDB secures €3.6m in investment
15 March 2021, The Irish Times

[MCR2030-CAMS-ARISE-UNDRR Webinar] Preventing cascading failures of critical assets: Using the Open-Source Critical Asset Management System (CAMS) to help cities become disaster and climate resilient
12 April 2022, United Nations Office for Disaster Risk Reduction

provided by Google News

Deepthi Sigireddi on Distributed Database Architecture in the Cloud Native Era
20 May 2024, InfoQ.com

PlanetScale raises $30M Series B for its database service
23 June 2021, TechCrunch

PlanetScale offers undo button to reverse schema migration without losing data
24 March 2022, The Register

PlanetScale launches new database-as-a-service platform
18 May 2021, TechTarget

PlanetScale Announces $30M Series B Funding to Accelerate Adoption of Instantly Provisioned and Infinitely Scalable Database
23 June 2021, Business Wire

provided by Google News

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