DBMS > Atos Standard Common Repository vs. Dolt vs. Heroic vs. LokiJS vs. Oracle Berkeley DB

System Properties Comparison Atos Standard Common Repository vs. Dolt vs. Heroic vs. LokiJS vs. Oracle Berkeley DB

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

A MySQL compatible DBMS with Git-like versioning of data and schema

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

In-memory JavaScript DBMS

Widely used in-process key-value store

Primary database model

Document store
Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Secondary database models

Document store

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

Score	1.02
Rank	#191	Overall
	#89	Relational DBMS

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	0.49
Rank	#260	Overall
	#42	Document stores

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

Website

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

github.com/dolthub/dolt
www.dolthub.com

github.com/spotify/heroic

github.com/techfort/LokiJS

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

Technical documentation

docs.dolthub.com

spotify.github.io/heroic

techfort.github.io/LokiJS

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

Developer

Atos Convergence Creators

DoltHub Inc

Spotify

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Initial release

2016

2018

2014

1994

Current release

1703

18.1.40, May 2020

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

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

Java

JavaScript

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

Server operating systems

Linux

Linux
macOS
Windows

server-less, requires a JavaScript environment (browser, Node.js)

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Data scheme

Schema and schema-less with LDAP views

yes

schema-free

Typing

predefined data types such as float or date

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

via Elasticsearch

yes

via views

yes

SQL

Support of SQL

yes

SQL interfaced based on SQLite is available

APIs and other access methods

LDAP

CLI Client
HTTP REST

HQL (Heroic Query Language, a JSON-based language)
HTTP API

JavaScript API

Supported programming languages

All languages with LDAP bindings

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

JavaScript

.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

Server-side scripts

Stored procedures

yes

currently in alpha release

View functions in JavaScript

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

A database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.

yes

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency
Immediate Consistency

none

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

ACID

atomic operations within a single collection possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

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

Only one user is configurable, and must be specified in the config file at startup

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More resources

DB-Engines blog posts

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

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