DBMS > Faircom DB vs. KairosDB vs. Manticore Search vs. Percona Server for MySQL vs. Yanza

System Properties Comparison Faircom DB vs. KairosDB vs. Manticore Search vs. Percona Server for MySQL vs. Yanza

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.

Distributed Time Series DBMS based on Cassandra or H2

Multi-storage database for search, including full-text search.

Enhanced drop-in replacement for MySQL based on XtraDB or TokuDB storage engines with improved performance and additional diagnostic and management features.

Time Series DBMS for IoT Applications

Primary database model

Key-value store
Relational DBMS

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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

Score	0.29
Rank	#304	Overall
	#43	Key-value stores
	#136	Relational DBMS

Score	0.67
Rank	#233	Overall
	#20	Time Series DBMS

Score	0.29
Rank	#302	Overall
	#21	Search engines

Score	2.10
Rank	#119	Overall
	#57	Relational DBMS

Website

www.faircom.com/products/faircom-db

github.com/kairosdb/kairosdb

manticoresearch.com

www.percona.com/software/mysql-database/percona-server

yanza.com

Technical documentation

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

kairosdb.github.io

manual.manticoresearch.com

www.percona.com/downloads/Percona-Server-LATEST

Developer

FairCom Corporation

Manticore Software

Percona

Yanza

Initial release

1979

2013

2017

2008

2015

Current release

V12, November 2020

1.2.2, November 2018

6.0, February 2023

8.0.36-28, 2024

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

Apache 2.0

Open Source

GPL version 2

Open Source

GPL version 2

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++

Java

C++

C and C++

Server operating systems

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

easily portable to other OSs

Linux
OS X
Windows

FreeBSD
Linux
macOS
Windows

Linux

Windows

Data scheme

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

schema-free

Fixed schema

yes

schema-free

Typing

predefined data types such as float or date

yes, ANSI SQL Types, JSON, typed binary structures

yes

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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 index from XML

yes

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

yes, ANSI SQL with proprietary extensions

SQL-like query language

yes

APIs and other access methods

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

Graphite protocol
HTTP REST
Telnet API

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

ADO.NET
JDBC
ODBC

HTTP API

Supported programming languages

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

Java
JavaScript

Node.js
PHP
Python

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

Ada
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

user defined functions

yes

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

based on Cassandra

Sharding

Partitioning is done manually, search queries against distributed index is supported

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

based on Cassandra

Synchronous replication based on Galera library

Multi-source replication
Source-replica replication
XtraDB Cluster

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

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

tunable from ACID to Eventually Consistent

yes

isolated transactions for atomic changes and binary logging for safe writes

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

The original contents of fields are not stored in the Manticore index.

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

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

simple password-based access control

Users with fine-grained authorization concept

no user groups or roles

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