DBMS > NSDb vs. Oracle Berkeley DB vs. STSdb vs. WakandaDB

System Properties Comparison NSDb vs. Oracle Berkeley DB vs. STSdb vs. WakandaDB

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Editorial information provided by DB-Engines

Name

Description

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

Widely used in-process key-value store

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Time Series DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Key-value store

Object oriented DBMS

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

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	2.01
Rank	#126	Overall
	#21	Key-value stores
	#3	Native XML DBMS

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Score	0.10
Rank	#356	Overall
	#16	Object oriented DBMS

Website

nsdb.io

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

github.com/STSSoft/STSdb4

wakanda.github.io

Technical documentation

nsdb.io/Architecture

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

wakanda.github.io/doc

Developer

Oracle

originally developed by Sleepycat, which was acquired by Oracle

STS Soft SC

Wakanda SAS

Initial release

2017

1994

2011

2012

Current release

18.1.40, May 2020

4.0.8, September 2015

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

commercial license available

Open Source

GPLv2, commercial license available

Open Source

AGPLv3, extended 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

Java, Scala

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

C++, JavaScript

Server operating systems

Linux
macOS

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes: int, bigint, decimal, string

yes

primitive types and user defined types (classes)

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.

yes

only with the Berkeley DB XML edition

Secondary indexes

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

gRPC
HTTP REST
WebSocket

.NET Client API

RESTful HTTP API

Supported programming languages

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

C#
Java

JavaScript

Server-side scripts

Stored procedures

yes

Triggers

yes

only for the SQL API

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

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

Foreign keys

Referential integrity

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

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

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