DBMS > Atos Standard Common Repository vs. DuckDB vs. Google Cloud Datastore vs. Newts

System Properties Comparison Atos Standard Common Repository vs. DuckDB vs. Google Cloud Datastore vs. Newts

Please select another system to include it in the comparison.

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

An embeddable, in-process, column-oriented SQL OLAP RDBMS

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

Time Series DBMS based on Cassandra

Primary database model

Document store
Key-value store

Relational DBMS

Document store

Time Series DBMS

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

Score	4.57
Rank	#74	Overall
	#40	Relational DBMS

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

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

duckdb.org

cloud.google.com/datastore

opennms.github.io/newts

Technical documentation

duckdb.org/docs

cloud.google.com/datastore/docs

github.com/OpenNMS/newts/wiki

Developer

Atos Convergence Creators

Google

OpenNMS Group

Initial release

2016

2018

2008

2014

Current release

1703

0.10, February 2024

License

Commercial or Open Source

commercial

Open Source

MIT License

commercial

Open Source

Apache 2.0

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

C++

Java

Server operating systems

Linux

server-less

hosted

Linux
OS X
Windows

Data scheme

Schema and schema-less with LDAP views

yes

schema-free

Typing

predefined data types such as float or date

optional

yes

yes, details here

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 query language (GQL)

APIs and other access methods

LDAP

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

HTTP REST
Java API

Supported programming languages

All languages with LDAP bindings

C
C#

3rd party driver
C++
Crystal

3rd party driver
Go

3rd party driver
Java
Lisp

3rd party driver
Python
R
Ruby

3rd party driver
Rust
Swift
Zig

3rd party driver

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Java

Server-side scripts

Stored procedures

using Google App Engine

Triggers

yes

Callbacks using the Google Apps Engine

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

none

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Multi-source replication using Paxos

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

Transaction concepts

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

Atomic execution of specific operations

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

My First Billion (of Rows) in DuckDB | by João Pedro | May, 2024
1 May 2024, Towards Data Science

Enabling Remote Query Execution through DuckDB Extensions
12 March 2024, InfoQ.com

DuckDB Walks to the Beat of Its Own Analytics Drum
5 March 2024, Datanami

MotherDuck Raises $52.5 Million Series B Funding as DuckDB Adoption Soars
20 September 2023, PR Newswire

Seattle startup MotherDuck raises $52.5M at a $400M valuation to fuel DuckDB analytics platform
20 September 2023, GeekWire

provided by Google News

Google Cloud Stops Exit Fees
12 January 2024, Spiceworks News and Insights

Best cloud storage of 2024
29 April 2024, TechRadar

BigID Data Intelligence Platform Now Available on Google Cloud Marketplace
6 November 2023, PR Newswire

Inside Google’s strategic move to eliminate customer cloud data transfer fees
12 January 2024, Network World

What is Google App Engine? | Definition from TechTarget
26 April 2024, TechTarget

provided by Google News

Farewell, Froggy: The Age of Ribbit Is Nearing an End
25 May 2013, Mother Jones

provided by Google News

Share this page