DBMS > BigchainDB vs. mSQL vs. NSDb vs. Spark SQL vs. Transwarp KunDB

System Properties Comparison BigchainDB vs. mSQL vs. NSDb vs. Spark SQL vs. Transwarp KunDB

Editorial information provided by DB-Engines

Name

Description

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

mSQL (Mini SQL) is a simple and lightweight RDBMS

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Spark SQL is a component on top of 'Spark Core' for structured data processing

OLTP DBMS based on a distributed architecture and highly compatible with MySQL and Oracle

Primary database model

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

Score	0.85
Rank	#208	Overall
	#35	Document stores

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	0.14
Rank	#341	Overall
	#149	Relational DBMS

Website

www.bigchaindb.com

hughestech.com.au/products/msql

nsdb.io

spark.apache.org/sql

www.transwarp.cn/en/product/kundb

Technical documentation

bigchaindb.readthedocs.io/en/latest

nsdb.io/Architecture

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Hughes Technologies

Apache Software Foundation

Transwarp

Initial release

2016

1994

2017

2014

Current release

4.4, October 2021

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

Open Source

AGPL v3

commercial

free licenses can be provided

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Python

Java, Scala

Scala

Server operating systems

Linux

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
macOS

Linux
OS X
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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.

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

SQL-like query language

SQL-like DML and DDL statements

yes

APIs and other access methods

CLI Client
RESTful HTTP API

JDBC
ODBC

gRPC
HTTP REST
WebSocket

JDBC
ODBC

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

C
C++
Delphi
Java
Perl
PHP
Tcl

Java
Scala

Java
Python
R
Scala

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

yes, utilizing Spark Core

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

yes

Using Apache Lucene

yes

In-memory capabilities

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

User concepts

Access control

yes

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More resources

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