DBMS > Databend vs. Oracle Berkeley DB vs. Oracle NoSQL vs. Oracle Rdb

System Properties Comparison Databend vs. Oracle Berkeley DB vs. Oracle NoSQL vs. Oracle Rdb

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Editorial information provided by DB-Engines

Name

Description

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

Widely used in-process key-value store

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Primary database model

Relational DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Document store
Key-value store
Relational DBMS

Relational DBMS

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

Score	0.28
Rank	#287	Overall
	#131	Relational DBMS

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

Score	3.07
Rank	#86	Overall
	#15	Document stores
	#11	Key-value stores
	#47	Relational DBMS

Score	1.04
Rank	#184	Overall
	#84	Relational DBMS

Website

github.com/datafuselabs/databend
www.databend.com

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

www.oracle.com/database/nosql/technologies/nosql

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

Technical documentation

docs.databend.com

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

docs.oracle.com/en/database/other-databases/nosql-database/index.html

www.oracle.com/database/technologies/related/rdb-doc.html

Developer

Databend Labs

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Oracle

Oracle, originally developed by Digital Equipment Corporation (DEC)

Initial release

2021

1994

2011

1984

Current release

1.0.59, April 2023

18.1.40, May 2020

24.1, May 2024

7.4.1.1, 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

commercial license available

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

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

Rust

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

Java

Server operating systems

hosted
Linux
macOS

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux
Solaris SPARC/x86

HP Open VMS

Data scheme

yes

schema-free

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

Flexible Schema (defined schema, partial schema, schema free)

Typing

predefined data types such as float or date

yes

optional

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

SQL

Support of SQL

yes

SQL interfaced based on SQLite is available

SQL-like DML and DDL statements

yes

APIs and other access methods

CLI Client
JDBC
RESTful HTTP API

RESTful HTTP API

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
Rust

.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
C#
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

configurable

ACID within a storage node (=shard)

yes, on a single node

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

off heap cache

User concepts

Access control

Users with fine-grained authorization concept, user roles

Access rights for users and roles

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