DBMS > Atos Standard Common Repository vs. BigchainDB vs. Brytlyt vs. Ingres vs. Microsoft Azure Cosmos DB

System Properties Comparison Atos Standard Common Repository vs. BigchainDB vs. Brytlyt vs. Ingres vs. Microsoft Azure Cosmos 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

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

Well established RDBMS

Globally distributed, horizontally scalable, multi-model database service

Primary database model

Document store
Key-value store

Document store

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Spatial DBMS

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

Score	0.85
Rank	#208	Overall
	#35	Document stores

Score	0.38
Rank	#276	Overall
	#127	Relational DBMS

Score	3.80
Rank	#82	Overall
	#44	Relational DBMS

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Website

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

www.bigchaindb.com

brytlyt.io

www.actian.com/databases/ingres

azure.microsoft.com/services/cosmos-db

Technical documentation

bigchaindb.readthedocs.io/en/latest

docs.brytlyt.io

docs.actian.com/ingres

learn.microsoft.com/azure/cosmos-db

Developer

Atos Convergence Creators

Brytlyt

Actian Corporation

Microsoft

Initial release

2016

1974

originally developed at University Berkely in early 1970s

2014

Current release

1703

5.0, August 2023

11.2, May 2022

License

Commercial or Open Source

commercial

Open Source

AGPL v3

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Python

C, C++ and CUDA

Server operating systems

Linux

Linux
OS X
Windows

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

hosted

Data scheme

Schema and schema-less with LDAP views

schema-free

yes

schema-free

Typing

predefined data types such as float or date

optional

yes

JSON types

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

specific XML-type available, but no XML query functionality.

but tools for importing/exporting data from/to XML-files available

Secondary indexes

yes

All properties auto-indexed by default

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

LDAP

CLI Client
RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

Supported programming languages

All languages with LDAP bindings

Go
Haskell
Java
JavaScript
Python
Ruby

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

yes

JavaScript

Triggers

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

horizontal partitioning

Ingres Star to access multiple databases simultaneously

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Source-replica replication

Ingres Replicator

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session 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

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

Durability

Support for making data persistent

yes

yes,with MongoDB ord RethinkDB

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

yes

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

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