DBMS > 4D vs. Atos Standard Common Repository vs. IRONdb vs. Qdrant vs. Tkrzw

System Properties Comparison 4D vs. Atos Standard Common Repository vs. IRONdb vs. Qdrant vs. Tkrzw

Editorial information provided by DB-Engines

Name

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

IRONdb seems to be discontinued. Therefore it is excluded 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 distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

A high-performance vector database with neural network or semantic-based matching

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Relational DBMS

Document store
Key-value store

Time Series DBMS

Vector DBMS

Key-value store

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	1.16
Rank	#175	Overall
	#6	Vector DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

www.4d.com

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

www.circonus.com/solutions/time-series-database/

github.com/qdrant/qdrant
qdrant.tech

dbmx.net/tkrzw

Technical documentation

developer.4d.com

docs.circonus.com/irondb/category/getting-started

qdrant.tech/documentation

Developer

4D, Inc

Atos Convergence Creators

Circonus LLC.

Qdrant

Mikio Hirabayashi

Initial release

1984

2016

2017

2021

2020

Current release

v20, April 2023

1703

V0.10.20, January 2018

0.9.3, August 2020

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

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

C and C++

Rust

C++

Server operating systems

OS X
Windows

Linux

Docker
Linux
macOS
Windows

Linux
macOS

Data scheme

yes

Schema and schema-less with LDAP views

schema-free

Typing

predefined data types such as float or date

yes

optional

yes

text, numeric, histograms

Numbers, Strings, Geo, Boolean

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

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

yes

close to SQL 92

SQL-like query language (Circonus Analytics Query Language: CAQL)

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

LDAP

HTTP API

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

Supported programming languages

4D proprietary IDE
PHP

All languages with LDAP bindings

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

yes

yes, in Lua

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

cell division

Automatic, metric affinity per node

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

configurable replication factor, datacenter aware

Collection-level replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate consistency per node, eventual consistency across nodes

Eventual Consistency, tunable consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic execution of specific operations

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

using specific database classes

User concepts

Access control

Users and groups

LDAP bind authentication

Key-based authentication

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More resources

DB-Engines blog posts

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