DBMS > OrigoDB vs. TigerGraph vs. Vitess vs. Yanza

System Properties Comparison OrigoDB vs. TigerGraph vs. Vitess vs. Yanza

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Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

A fully ACID in-memory object graph database

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Scalable, distributed, cloud-native DBMS, extending MySQL

Time Series DBMS for IoT Applications

Primary database model

Document store
Object oriented DBMS

Graph DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Score	0.88
Rank	#203	Overall
	#95	Relational DBMS

Website

origodb.com

www.tigergraph.com

vitess.io

yanza.com

Technical documentation

origodb.com/docs

docs.tigergraph.com

vitess.io/docs

Developer

Robert Friberg et al

The Linux Foundation, PlanetScale

Yanza

Initial release

2009

under the name LiveDB

2017

2013

2015

Current release

15.0.2, December 2022

License

Commercial or Open Source

Open Source

commercial

Open Source

Apache Version 2.0, commercial licenses available

commercial

free version available

Cloud-based only

Only available as a cloud service

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Server operating systems

Linux
Windows

Linux

Docker
Linux
macOS

Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language (GSQL)

yes

with proprietary extensions

APIs and other access methods

.NET Client API
HTTP API
LINQ

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

ADO.NET
JDBC
MySQL protocol
ODBC

HTTP API

Supported programming languages

.Net

C++
Java

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

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

proprietary syntax

Triggers

yes

Domain Events

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

client side managed; servers are not synchronized

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency across shards
Immediate Consistency within a shard

Immediate Consistency

Foreign keys

Referential integrity

depending on model

yes

Relationships in graphs

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

yes

Durability

Support for making data persistent

yes

Write ahead log

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 authorization

Role-based access control

Users with fine-grained authorization concept

no user groups or roles

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