DBMS > Atos Standard Common Repository vs. Google Cloud Datastore vs. HyperSQL vs. KairosDB

System Properties Comparison Atos Standard Common Repository vs. Google Cloud Datastore vs. HyperSQL vs. KairosDB

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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

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

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Distributed Time Series DBMS based on Cassandra or H2

Primary database model

Document store
Key-value store

Document store

Relational DBMS

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	3.49
Rank	#87	Overall
	#47	Relational DBMS

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Website

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

cloud.google.com/datastore

hsqldb.org

github.com/kairosdb/kairosdb

Technical documentation

cloud.google.com/datastore/docs

hsqldb.org/web/hsqlDocsFrame.html

kairosdb.github.io

Developer

Atos Convergence Creators

Google

Initial release

2016

2008

2001

2013

Current release

1703

2.7.2, June 2023

1.2.2, November 2018

License

Commercial or Open Source

commercial

Open Source

based on BSD license

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

Server operating systems

Linux

hosted

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Linux
OS X
Windows

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

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

SQL-like query language (GQL)

yes

APIs and other access methods

LDAP

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

HTTP API

JDBC via HTTP
JDBC
ODBC

Graphite protocol
HTTP REST
Telnet API

Supported programming languages

All languages with LDAP bindings

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

All languages supporting JDBC/ODBC
Java

Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

using Google App Engine

Java, SQL

Triggers

yes

Callbacks using the Google Apps Engine

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

none

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication using Paxos

none

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 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.

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

ACID

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

User concepts

Access control

LDAP bind authentication

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

fine grained access rights according to SQL-standard

simple password-based access control

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