DBMS > Amazon DynamoDB vs. Atos Standard Common Repository vs. BigchainDB vs. Brytlyt vs. Ingres

System Properties Comparison Amazon DynamoDB vs. Atos Standard Common Repository vs. BigchainDB vs. Brytlyt vs. Ingres

Editorial information provided by DB-Engines

Name

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

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

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

Primary database model

Document store
Key-value store

Document store

Relational DBMS

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

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

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

Website

aws.amazon.com/dynamodb

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

www.bigchaindb.com

brytlyt.io

www.actian.com/databases/ingres

Technical documentation

docs.aws.amazon.com/dynamodb

bigchaindb.readthedocs.io/en/latest

docs.brytlyt.io

docs.actian.com/ingres

Developer

Amazon

Atos Convergence Creators

Brytlyt

Actian Corporation

Initial release

2012

2016

1974

originally developed at University Berkely in early 1970s

Current release

1703

5.0, August 2023

11.2, May 2022

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

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

hosted

Linux

Linux
OS X
Windows

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

Schema and schema-less with LDAP views

schema-free

yes

Typing

predefined data types such as float or date

yes

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

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

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

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP API

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)

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

All languages with LDAP bindings

Go
Haskell
Java
JavaScript
Python
Ruby

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

yes

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

horizontal partitioning

Ingres Star to access multiple databases simultaneously

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Source-replica replication

Ingres Replicator

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

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

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

LDAP bind authentication

yes

fine grained access rights according to SQL-standard

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