DBMS > Atos Standard Common Repository vs. Graph Engine vs. Riak TS vs. Trino

System Properties Comparison Atos Standard Common Repository vs. Graph Engine vs. Riak TS vs. Trino

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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 distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Fast distributed SQL query engine for big data analytics. Forked from Presto and originally named PrestoSQL

Primary database model

Document store
Key-value store

Graph DBMS
Key-value store

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Key-value store
Spatial DBMS
Search engine
Time Series DBMS
Wide column store

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

Score	0.56
Rank	#241	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	0.17
Rank	#318	Overall
	#27	Time Series DBMS

Score	5.28
Rank	#61	Overall
	#35	Relational DBMS

Website

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

www.graphengine.io

trino.io

Technical documentation

www.graphengine.io/docs/manual

www.tiot.jp/riak-docs/riak/ts/latest

trino.io/broadcast
trino.io/docs/current

Developer

Atos Convergence Creators

Microsoft

Open Source, formerly Basho Technologies

Trino Software Foundation

Initial release

2016

2010

2015

2012

2020 rebranded from PrestoSQL

Current release

1703

3.0.0, September 2022

License

Commercial or Open Source

commercial

Open Source

MIT License

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

.NET and C

Erlang

Java

Server operating systems

Linux

.NET

Linux
OS X

Linux
macOS

for devlopment

Data scheme

Schema and schema-less with LDAP views

yes

schema-free

yes

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

restricted

depending on connected data-source

SQL

Support of SQL

yes, limited

yes

APIs and other access methods

LDAP

RESTful HTTP API

HTTP API
Native Erlang Interface

JDBC
RESTful HTTP API
Trino CLI

Supported programming languages

All languages with LDAP bindings

C#
C++
F#
Visual Basic

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

yes

Erlang

yes, depending on connected data-source

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

horizontal partitioning

Sharding

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

depending on connected data-source

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

depending on connected data-source

Foreign keys

Referential integrity

links between datasets can be stored

Transaction concepts

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

Atomic execution of specific operations

depending on connected data-source

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

depending on connected data-source

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

SQL standard access control

More information provided by the system vendor

News

23 is a go, keeping pace with Java
17 September 2024

65: Performance boosts
12 September 2024

64: Control with Open Policy Agent OPA
22 August 2024

63: Querying with JS
1 August 2024

62: A lakehouse that simply works at Prezi
11 July 2024

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