DBMS > Atos Standard Common Repository vs. Google Cloud Datastore vs. Rockset vs. Sadas Engine vs. SWC-DB

System Properties Comparison Atos Standard Common Repository vs. Google Cloud Datastore vs. Rockset vs. Sadas Engine vs. SWC-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

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

A scalable, reliable search and analytics service in the cloud, built on RocksDB

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

A high performance, scalable Wide Column DBMS

Primary database model

Document store
Key-value store

Document store

Relational DBMS

Wide column store

Secondary database models

Relational DBMS
Search engine

Time Series DBMS

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

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	0.79
Rank	#211	Overall
	#35	Document stores

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

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

cloud.google.com/datastore

rockset.com

www.sadasengine.com

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

Technical documentation

cloud.google.com/datastore/docs

docs.rockset.com

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Atos Convergence Creators

Google

Rockset

SADAS s.r.l.

Alex Kashirin

Initial release

2016

2008

2019

2006

2020

Current release

1703

8.0

0.5, April 2021

License

Commercial or Open Source

commercial

free trial version available

Open Source

GPL V3

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++

Server operating systems

Linux

hosted

AIX
Linux
Windows

Linux

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, details here

dynamic typing

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

ingestion from XML files supported

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language (GQL)

Read-only SQL queries, including JOINs

yes

SQL-like query language

APIs and other access methods

LDAP

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

HTTP REST

JDBC
ODBC
Proprietary protocol

Proprietary protocol
Thrift

Supported programming languages

All languages with LDAP bindings

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

Go
Java
JavaScript (Node.js)
Python

.Net
C
C#
C++
Groovy
Java
PHP
Python

C++

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

Sharding

Automatic sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication using Paxos

yes

none

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 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

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

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

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

managed by 'Learn by Usage'

User concepts

Access control

LDAP bind authentication

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

Access rights for users and organizations can be defined via Rockset console

Access rights for users, groups and roles according to SQL-standard

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