DBMS > Atos Standard Common Repository vs. Dolt vs. Hive vs. SWC-DB

System Properties Comparison Atos Standard Common Repository vs. Dolt vs. Hive vs. SWC-DB

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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

data warehouse software for querying and managing large distributed datasets, built on Hadoop

A high performance, scalable Wide Column DBMS

Primary database model

Document store
Key-value store

Relational DBMS

Wide column store

Secondary database models

Document store

Time Series DBMS

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

Score	0.96
Rank	#193	Overall
	#90	Relational DBMS

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

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

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

hive.apache.org

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

docs.dolthub.com

cwiki.apache.org/confluence/display/Hive/Home

Developer

Atos Convergence Creators

DoltHub Inc

Apache Software Foundation

initially developed by Facebook

Alex Kashirin

Initial release

2016

2018

2012

2020

Current release

1703

3.1.3, April 2022

0.5, April 2021

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache Version 2

Open Source

GPL V3

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++

Server operating systems

Linux

Linux
macOS
Windows

All OS with a Java VM

Linux

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

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

SQL-like query language

APIs and other access methods

LDAP

CLI Client
HTTP REST

JDBC
ODBC
Thrift

Proprietary protocol
Thrift

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

C++
Java
PHP
Python

C++

Server-side scripts

Stored procedures

yes

currently in alpha release

yes

user defined functions and integration of map-reduce

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

none

Sharding

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.

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

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

LDAP bind authentication

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

Access rights for users, groups and roles

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