DBMS > 4D vs. BigObject vs. IRONdb vs. RisingWave

System Properties Comparison 4D vs. BigObject vs. IRONdb vs. RisingWave

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Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Application development environment with integrated database management system

Analytic DBMS for real-time computations and queries

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

A distributed RDBMS for stream processing, wire-compatible with PostgreSQL

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Time Series DBMS

Relational DBMS

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	0.58
Rank	#242	Overall
	#111	Relational DBMS

Website

www.4d.com

bigobject.io

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

www.risingwave.com/database

Technical documentation

developer.4d.com

docs.bigobject.io

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

docs.risingwave.com/docs/current/intro

Developer

4D, Inc

BigObject, Inc.

Circonus LLC.

RisingWave Labs

Initial release

1984

2015

2017

2022

Current release

v20, April 2023

V0.10.20, January 2018

1.2, September 2023

License

Commercial or Open Source

commercial

free community edition available

commercial

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

C and C++

Rust

Server operating systems

OS X
Windows

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux

Docker
Linux
macOS

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

text, numeric, histograms

Standard SQL-types and JSON

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

yes

close to SQL 92

SQL-like DML and DDL statements

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

yes

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

fluentd
ODBC
RESTful HTTP API

HTTP API

JDBC
PostgreSQL wire protocol

Supported programming languages

4D proprietary IDE
PHP

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

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Lua

yes, in Lua

UDFs in Python or Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Automatic, metric affinity per node

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

configurable replication factor, datacenter aware

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate consistency per node, eventual consistency across nodes

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

Users and groups

Users and Roles

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More resources

DB-Engines blog posts

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