DBMS > BigchainDB vs. DolphinDB vs. NSDb vs. Oracle Berkeley DB

System Properties Comparison BigchainDB vs. DolphinDB vs. NSDb vs. Oracle Berkeley DB

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Editorial information provided by DB-Engines

Name

Description

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

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

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

Widely used in-process key-value store

Primary database model

Document store

Time Series DBMS
Vector DBMS

Time Series DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Secondary database models

Relational DBMS

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

Score	0.76
Rank	#216	Overall
	#36	Document stores

Score	2.72
Rank	#100	Overall
	#8	Time Series DBMS
	#5	Vector DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	1.88
Rank	#130	Overall
	#23	Key-value stores
	#3	Native XML DBMS

Website

www.bigchaindb.com

www.dolphindb.com

nsdb.io

www.oracle.com/database/technologies/related/berkeleydb.html

Technical documentation

bigchaindb.readthedocs.io/en/latest

docs.dolphindb.cn/en/help200/index.html

nsdb.io/Architecture

docs.oracle.com/cd/E17076_05/html/index.html

Developer

DolphinDB, Inc

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Initial release

2016

2018

2017

1994

Current release

v2.00.4, January 2022

18.1.40, May 2020

License

Commercial or Open Source

Open Source

AGPL v3

commercial

free community version available

Open Source

Apache Version 2.0

Open Source

commercial license available

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

C++

Java, Scala

C, Java, C++ (depending on the Berkeley DB edition)

Server operating systems

Linux

Linux
Windows

Linux
macOS

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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

only with the Berkeley DB XML edition

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

SQL interfaced based on SQLite is available

APIs and other access methods

CLI Client
RESTful HTTP API

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

gRPC
HTTP REST
WebSocket

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

Java
Scala

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

Server-side scripts

Stored procedures

yes

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

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.

yes

User concepts

Access control

yes

Administrators, Users, Groups

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More resources

Recent citations in the news

Using BigchainDB: A Database with Blockchain Characteristics
20 January 2022, Open Source For You

7 blockchain firms join Bosch led GAIA-X consortium for vehicle identity
13 September 2022, Ledger Insights

What is BigchainDB Technology & How it works and the Characteristics?
26 August 2017, Blockchain Council

How to use blockchain to build a database solution
2 March 2017, ZDNet

BigchainDB: A Popular and Powerful Database for Blockchain
9 September 2019, Open Source For You

provided by Google News

What is NoSQL (Not Only SQL database)?
28 February 2022, TechTarget

Margo I. Seltzer
18 August 2020, Berkman Klein Center

Oracle acquires Sleepycat for code
17 August 2016, East Bay Times

Database Trends Report: SQL Beats NoSQL, MySQL Most Popular
5 March 2019, ADT Magazine

How to store financial market data for backtesting
26 January 2019, Towards Data Science

provided by Google News

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