DBMS > Atos Standard Common Repository vs. Oracle Berkeley DB vs. RDF4J vs. RRDtool vs. StarRocks

System Properties Comparison Atos Standard Common Repository vs. Oracle Berkeley DB vs. RDF4J vs. RRDtool vs. StarRocks

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

Widely used in-process key-value store

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

An open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics

Forked from Apache Doris

Primary database model

Document store
Key-value store

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

RDF store

Time Series DBMS

Relational DBMS

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	0.74
Rank	#222	Overall
	#9	RDF stores

Score	1.90
Rank	#132	Overall
	#11	Time Series DBMS

Score	0.93
Rank	#198	Overall
	#93	Relational DBMS

Website

atos.net/en/convergence-creators/portfolio/standard-common-repository

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

rdf4j.org

oss.oetiker.ch/rrdtool

www.starrocks.io

Technical documentation

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

rdf4j.org/documentation

oss.oetiker.ch/rrdtool/doc

docs.starrocks.io/en-us/latest/introduction/StarRocks_intro

Developer

Atos Convergence Creators

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Tobias Oetiker

The Linux Foundation

since Feb 2023

Initial release

2016

1994

2004

1999

2020

Current release

1703

18.1.40, May 2020

1.8.0, 2022

2.5.3, March 2023

License

Commercial or Open Source

commercial

Open Source

commercial license available

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

GPL V2 and FLOSS

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

Java

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

Java

Implementations in Java (e.g. RRD4J) and C# available

C++, Java

Server operating systems

Linux

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux
OS X
Unix
Windows

HP-UX
Linux

Linux

Data scheme

Schema and schema-less with LDAP views

schema-free

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

optional

yes

Numeric data only

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

Exporting into and restoring from XML files possible

Secondary indexes

yes

SQL

Support of SQL

yes

SQL interfaced based on SQLite is available

yes

APIs and other access methods

LDAP

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

in-process shared library
Pipes

JDBC
MySQL protocol

Supported programming languages

All languages with LDAP bindings

.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

Java
PHP
Python

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

Java

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

only for the SQL API

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

none

horizontal partitioning (by range and hash)

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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 or Eventual Consistency depending on configuration

none

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomic execution of specific operations

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

by using the rrdcached daemon

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

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

LDAP bind authentication

Role based access control and fine grained access rights

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

show all

Recent citations in the news

Margo Seltzer Named ACM Athena Lecturer for Technical and Mentoring Contributions
26 April 2023, HPCwire

ACM recognizes far-reaching technical achievements with special awards
26 May 2021, EurekAlert

Oracle buys Sleepycat Software
14 February 2006, MarketWatch

Database Trends Report: SQL Beats NoSQL, MySQL Most Popular -- ADTmag
5 March 2019, ADT Magazine

Margo I. Seltzer | Berkman Klein Center
18 August 2020, Berkman Klein Center

provided by Google News

GraphDB Goes Open Source
27 January 2020, iProgrammer

Ontotext's GraphDB 8.10 Makes Knowledge Graph Experience Faster and Richer
13 June 2019, Markets Insider

provided by Google News

Critical IP spoofing bug patched in Cacti
15 December 2022, The Daily Swig

Cacti servers under attack by attackers exploiting CVE-2022-46169
16 January 2023, Help Net Security

How to install Cacti SNMP Monitor on Ubuntu
24 November 2017, TechRepublic

Installation Guide for Collectd and Collectd-Web to Monitor Server Resources in Linux
29 November 2017, Linux.com

The 16 Best Open Source Network Monitoring Tools in 2023
21 October 2022, Solutions Review

provided by Google News

StarRocks analytical DB heads to Linux Foundation
14 February 2023, VentureBeat

StarRocks Brings Speedy OLAP Database to the Cloud
14 July 2022, Datanami

StarRocks Launches Beta of Cloud Service for Its Analytics Engine
15 July 2022, The New Stack

StarRocks' real-time analytics engine moves to the cloud
14 July 2022, SiliconANGLE News

StarRocks Launches the Industry's Fastest, Cloud Native, Real-time Analytics Engine
14 July 2022, GlobeNewswire

provided by Google News

Share this page