DBMS > Amazon Redshift vs. BigchainDB vs. Faircom DB vs. LeanXcale

System Properties Comparison Amazon Redshift vs. BigchainDB vs. Faircom DB vs. LeanXcale

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

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

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Primary database model

Relational DBMS

Document store

Key-value store
Relational DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	0.85
Rank	#208	Overall
	#35	Document stores

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

Score	0.36
Rank	#280	Overall
	#40	Key-value stores
	#129	Relational DBMS

Website

aws.amazon.com/redshift

www.bigchaindb.com

www.faircom.com/products/faircom-db

www.leanxcale.com

Technical documentation

docs.aws.amazon.com/redshift

bigchaindb.readthedocs.io/en/latest

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

Developer

Amazon (based on PostgreSQL)

FairCom Corporation

LeanXcale

Initial release

2012

2016

1979

2015

Current release

V12, November 2020

License

Commercial or Open Source

commercial

Open Source

AGPL v3

commercial

Restricted, free version available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Python

ANSI C, C++

Server operating systems

hosted

Linux

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

easily portable to other OSs

Data scheme

yes

schema-free

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

yes

Typing

predefined data types such as float or date

yes

yes, ANSI SQL Types, JSON, typed binary structures

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

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes, ANSI SQL with proprietary extensions

yes

through Apache Derby

APIs and other access methods

JDBC
ODBC

CLI Client
RESTful HTTP API

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

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

Supported programming languages

All languages supporting JDBC/ODBC

Go
Haskell
Java
JavaScript
Python
Ruby

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

C
Java
Scala

Server-side scripts

Stored procedures

user defined functions

in Python

yes

.Net, JavaScript, C/C++

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

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

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

tunable from ACID to Eventually Consistent

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes,with MongoDB ord RethinkDB

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

User concepts

Access control

fine grained access rights according to SQL-standard

yes

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

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