DBMS > Faircom DB vs. Infobright vs. Postgres-XL vs. XTDB vs. Yanza

System Properties Comparison Faircom DB vs. Infobright vs. Postgres-XL vs. XTDB 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.

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

A general purpose database with bitemporal SQL and Datalog and graph queries

Time Series DBMS for IoT Applications

Primary database model

Key-value store
Relational DBMS

Relational DBMS

Document store

Time Series DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.18
Rank	#314	Overall
	#45	Key-value stores
	#141	Relational DBMS

Score	0.88
Rank	#198	Overall
	#92	Relational DBMS

Score	0.43
Rank	#260	Overall
	#119	Relational DBMS

Score	0.13
Rank	#330	Overall
	#45	Document stores

Website

www.faircom.com/products/faircom-db

ignitetech.com/softwarelibrary/infobrightdb

www.postgres-xl.org

github.com/xtdb/xtdb
www.xtdb.com

yanza.com

Technical documentation

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

www.postgres-xl.org/documentation

www.xtdb.com/docs

Developer

FairCom Corporation

Ignite Technologies Inc.; formerly InfoBright Inc.

Juxt Ltd.

Yanza

Initial release

1979

2005

2014

since 2012, originally named StormDB

2019

2015

Current release

V13, July 2024

10 R1, October 2018

1.19, September 2021

License

Commercial or Open Source

commercial

Restricted, free version available

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

Open Source

Mozilla public license

Open Source

MIT License

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++

Clojure

Server operating systems

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

easily portable to other OSs

Linux
Windows

Linux
macOS

All OS with a Java 8 (and higher) VM
Linux

Windows

Data scheme

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

yes

schema-free

Typing

predefined data types such as float or date

yes, ANSI SQL Types, JSON, typed binary structures

yes

yes, extensible-data-notation format

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.

yes

XML type, but no XML query functionality

Secondary indexes

yes

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

yes, ANSI SQL with proprietary extensions

yes

distributed, parallel query execution

limited SQL, making use of Apache Calcite

APIs and other access methods

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

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

HTTP REST
JDBC

HTTP API

Supported programming languages

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

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

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Clojure
Java

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

user defined 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

none

horizontal partitioning

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).

Source-replica replication

yes, each node contains all data

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

Transaction concepts

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

tunable from ACID to Eventually Consistent

ACID

MVCC

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

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

fine grained access rights according to SQL-standard

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