DBMS > 4D vs. Atos Standard Common Repository vs. Oracle Coherence vs. QuestDB vs. Riak KV

System Properties Comparison 4D vs. Atos Standard Common Repository vs. Oracle Coherence vs. QuestDB vs. Riak KV

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

Oracles in-memory data grid solution

A high performance open source SQL database for time series data

Distributed, fault tolerant key-value store

Primary database model

Relational DBMS

Document store
Key-value store

Key-value store

Time Series DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Secondary database models

Relational DBMS

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	1.92
Rank	#130	Overall
	#22	Key-value stores

Score	2.52
Rank	#109	Overall
	#9	Time Series DBMS

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Website

www.4d.com

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

www.oracle.com/java/coherence

questdb.io

Technical documentation

developer.4d.com

docs.oracle.com/en/middleware/standalone/coherence

questdb.io/docs

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

Developer

4D, Inc

Atos Convergence Creators

Oracle

QuestDB Technology Inc

OpenSource, formerly Basho Technologies

Initial release

1984

2016

2007

2014

2009

Current release

v20, April 2023

1703

14.1, August 2023

3.2.0, December 2022

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache version 2, commercial enterprise edition

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

Java (Zero-GC), C++, Rust

Erlang

Server operating systems

OS X
Windows

Linux

All OS with a Java VM

Linux
macOS
Windows

Linux
OS X

Data scheme

yes

Schema and schema-less with LDAP views

schema-free

yes

schema-free via InfluxDB Line Protocol

schema-free

Typing

predefined data types such as float or date

yes

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

SQL

Support of SQL

yes

close to SQL 92

SQL with time-series extensions

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

LDAP

JCache
JPA
RESTful HTTP API

HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol

HTTP API
Native Erlang Interface

Supported programming languages

4D proprietary IDE
PHP

All languages with LDAP bindings

.Net
C++
Java

PostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust

over HTTP

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

Server-side scripts

Stored procedures

yes

Erlang

Triggers

yes

Live Events

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

cell division

Sharding

horizontal partitioning (by timestamps)

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

yes, with selectable consistency level

Source-replica replication with eventual consistency

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency
Immediate Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

Transaction concepts

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

ACID

Atomic execution of specific operations

configurable

ACID for single-table writes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

yes

In-memory capabilities

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

yes

through memory mapped files

User concepts

Access control

Users and groups

LDAP bind authentication

authentification to access the cache via certificates or http basic authentication

yes, using Riak Security

More information provided by the system vendor

Specific characteristics

Relational model with native time series support Column-based storage and time partitioned...
» more

Competitive advantages

High ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more

Typical application scenarios

Financial tick data Industrial IoT Application Metrics Monitoring
» more

Key customers

Banks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more

Licensing and pricing models

Open source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more

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5 April 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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