DBMS > Oracle Berkeley DB vs. RisingWave vs. SiriDB vs. Tkrzw

System Properties Comparison Oracle Berkeley DB vs. RisingWave vs. SiriDB vs. Tkrzw

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Editorial information provided by DB-Engines

Name

Description

Widely used in-process key-value store

A distributed RDBMS for stream processing, wire-compatible with PostgreSQL

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Relational DBMS

Time Series DBMS

Key-value store

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

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

Score	0.64
Rank	#238	Overall
	#110	Relational DBMS

Score	0.07
Rank	#378	Overall
	#42	Time Series DBMS

Score	0.07
Rank	#372	Overall
	#57	Key-value stores

Website

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

www.risingwave.com/database

siridb.com

dbmx.net/tkrzw

Technical documentation

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

docs.risingwave.com/docs/current/intro

docs.siridb.com

Developer

Oracle

originally developed by Sleepycat, which was acquired by Oracle

RisingWave Labs

Cesbit

Mikio Hirabayashi

Initial release

1994

2022

2017

2020

Current release

18.1.40, May 2020

1.2, September 2023

0.9.3, August 2020

License

Commercial or Open Source

Open Source

commercial license available

Open Source

Apache Version 2.0

Open Source

MIT License

Open Source

Apache Version 2.0

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

C++

Server operating systems

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Docker
Linux
macOS

Linux

Linux
macOS

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

Standard SQL-types and JSON

yes

Numeric data

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

yes

APIs and other access methods

JDBC
PostgreSQL wire protocol

HTTP API

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

Go
Java
JavaScript (Node.js)
Python

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

UDFs in Python or Java

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

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

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

using specific database classes

User concepts

Access control

Users and Roles

simple rights management via user accounts

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