DBMS > 4D vs. Atos Standard Common Repository vs. Ehcache vs. Google Cloud Datastore vs. LokiJS

System Properties Comparison 4D vs. Atos Standard Common Repository vs. Ehcache vs. Google Cloud Datastore vs. LokiJS

Editorial information provided by DB-Engines

Name

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

Description

Application development environment with integrated database management system

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

A widely adopted Java cache with tiered storage options

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

In-memory JavaScript DBMS

Primary database model

Relational DBMS

Document store
Key-value store

Key-value store

Document store

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

Score	2.47
Rank	#110	Overall
	#54	Relational DBMS

Score	4.64
Rank	#68	Overall
	#8	Key-value stores

Score	4.36
Rank	#72	Overall
	#12	Document stores

Score	0.49
Rank	#260	Overall
	#42	Document stores

Website

www.4d.com

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

www.ehcache.org

cloud.google.com/datastore

github.com/techfort/LokiJS

Technical documentation

developer.4d.com

www.ehcache.org/documentation

cloud.google.com/datastore/docs

techfort.github.io/LokiJS

Developer

4D, Inc

Atos Convergence Creators

Terracotta Inc, owned by Software AG

Google

Initial release

1984

2016

2009

2008

2014

Current release

v20, April 2023

1703

3.10.0, March 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available

commercial

Open Source

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

JavaScript

Server operating systems

OS X
Windows

Linux

All OS with a Java VM

hosted

server-less, requires a JavaScript environment (browser, Node.js)

Data scheme

yes

Schema and schema-less with LDAP views

schema-free

Typing

predefined data types such as float or date

yes

optional

yes

yes, details here

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

via views

SQL

Support of SQL

yes

close to SQL 92

SQL-like query language (GQL)

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

LDAP

JCache

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

JavaScript API

Supported programming languages

4D proprietary IDE
PHP

All languages with LDAP bindings

Java

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

JavaScript

Server-side scripts

Stored procedures

yes

using Google App Engine

View functions in JavaScript

Triggers

yes

Cache Event Listeners

Callbacks using the Google Apps Engine

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

cell division

Sharding

by using Terracotta Server

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

by using Terracotta Server

Multi-source replication using Paxos

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Tunable Consistency (Strong, Eventual, Weak)

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.

none

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

Transaction concepts

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

ACID

Atomic execution of specific operations

yes

supports JTA and can work as an XA resource

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

atomic operations within a single collection possible

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Users and groups

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

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Related products and services

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More resources

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