DBMS > EventStoreDB vs. Oracle Berkeley DB vs. Qdrant vs. VelocityDB

System Properties Comparison EventStoreDB vs. Oracle Berkeley DB vs. Qdrant vs. VelocityDB

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Editorial information provided by DB-Engines

Name

Description

Industrial-strength, open-source database solution built from the ground up for event sourcing.

Widely used in-process key-value store

A high-performance vector database with neural network or semantic-based matching

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

Primary database model

Event Store

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Vector DBMS

Graph DBMS
Object oriented DBMS

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

Score	1.10
Rank	#179	Overall
	#1	Event Stores

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

Score	1.16
Rank	#175	Overall
	#6	Vector DBMS

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

Website

www.eventstore.com

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

github.com/qdrant/qdrant
qdrant.tech

velocitydb.com

Technical documentation

developers.eventstore.com

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

qdrant.tech/documentation

velocitydb.com/UserGuide

Developer

Event Store Limited

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Qdrant

VelocityDB Inc

Initial release

2012

1994

2021

2011

Current release

21.2, February 2021

18.1.40, May 2020

7.x

License

Commercial or Open Source

Open Source

commercial license available

Open Source

Apache Version 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

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

Rust

Server operating systems

Linux
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Docker
Linux
macOS
Windows

Any that supports .NET

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

Numbers, Strings, Geo, 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.

yes

only with the Berkeley DB XML edition

Secondary indexes

yes

Keywords, numberic ranges, geo, full-text

yes

SQL

Support of SQL

yes

SQL interfaced based on SQLite is available

APIs and other access methods

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

.Net

Supported programming languages

.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
Go
Java
JavaScript (Node.js)
Python
Rust

.Net

Server-side scripts

Stored procedures

Triggers

yes

only for the SQL API

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Collection-level replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency, tunable 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

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

Key-based authentication

Based on Windows Authentication

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