DBMS > Manticore Search vs. Oracle Berkeley DB vs. VelocityDB vs. WakandaDB

System Properties Comparison Manticore Search vs. Oracle Berkeley DB vs. VelocityDB vs. WakandaDB

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Editorial information provided by DB-Engines

Name

Description

Multi-storage database for search, including full-text search.

Widely used in-process key-value store

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

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

Primary database model

Search engine

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Graph DBMS
Object oriented DBMS

Object oriented DBMS

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Score	0.05
Rank	#358	Overall
	#36	Graph DBMS
	#16	Object oriented DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

manticoresearch.com

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

velocitydb.com

wakanda.github.io

Technical documentation

manual.manticoresearch.com

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

velocitydb.com/UserGuide

wakanda.github.io/doc

Developer

Manticore Software

Oracle

originally developed by Sleepycat, which was acquired by Oracle

VelocityDB Inc

Wakanda SAS

Initial release

2017

1994

2011

2012

Current release

6.0, February 2023

18.1.40, May 2020

7.x

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

GPL version 2

Open Source

commercial license available

commercial

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

C++

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

C++, JavaScript

Server operating systems

FreeBSD
Linux
macOS
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Any that supports .NET

Linux
OS X
Windows

Data scheme

Fixed schema

schema-free

yes

Typing

predefined data types such as float or date

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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.

Can index from XML

yes

only with the Berkeley DB XML edition

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

SQL-like query language

yes

SQL interfaced based on SQLite is available

APIs and other access methods

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

.Net

RESTful HTTP API

Supported programming languages

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

.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

.Net

JavaScript

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

only for the SQL API

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Partitioning is done manually, search queries against distributed index is supported

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication based on Galera library

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

isolated transactions for atomic changes and binary logging for safe writes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Manticore index.

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

Based on Windows Authentication

yes

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