DBMS > Faircom DB vs. Galaxybase vs. InfluxDB vs. Yanza

System Properties Comparison Faircom DB vs. Galaxybase vs. InfluxDB 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

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

Scalable, ACID-compliant native distributed parallel graph platform

DBMS for storing time series, events and metrics

Time Series DBMS for IoT Applications

Primary database model

Key-value store
Relational DBMS

Graph DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

with GEO package

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

Score	0.20
Rank	#318	Overall
	#48	Key-value stores
	#141	Relational DBMS

Score	0.00
Rank	#383	Overall
	#39	Graph DBMS

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Website

www.faircom.com/products/faircom-db

galaxybase.com

www.influxdata.com/products/influxdb-overview

yanza.com

Technical documentation

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

docs.influxdata.com/influxdb

Developer

FairCom Corporation

Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司

Yanza

Initial release

1979

2017

2013

2015

Current release

V12, November 2020

Nov 20, November 2021

2.7.6, April 2024

License

Commercial or Open Source

commercial

Restricted, free version available

commercial

Open Source

MIT-License; commercial enterprise version 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

ANSI C, C++

C and Java

Server operating systems

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

Linux

Linux
OS X

through Homebrew

Windows

Data scheme

schema free, schema optional, schema required, partial schema,

Strong typed schema

schema-free

Typing

predefined data types such as float or date

yes, ANSI SQL Types, JSON, typed binary structures

yes

Numeric data and Strings

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

yes, ANSI SQL with proprietary extensions

SQL-like query language

APIs and other access methods

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API

HTTP API
JSON over UDP

HTTP API

Supported programming languages

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

Go
Java
Python

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

user defined procedures and functions

Triggers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Sharding

in enterprise version only

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

selectable replication factor

in enterprise version only

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

tunable from ACID to Eventually Consistent

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Yes, tunable from durable to delayed durability to in-memory

yes

In-memory capabilities

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

yes

Depending on used storage engine

User concepts

Access control

Fine grained access rights according to SQL-standard with additional protections for files

Role-based access control

simple rights management via user accounts

More information provided by the system vendor

Specific characteristics

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Key customers

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Market metrics

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Licensing and pricing models

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

DB-Engines blog posts

Why Build a Time Series Data Platform?
20 July 2017, Paul Dix (guest author)

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Recent citations in the news

FairCom kicks off new era of database technology USA - English
10 November 2020, PR Newswire

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