DBMS > 4D vs. FatDB vs. HarperDB vs. Heroic

System Properties Comparison 4D vs. FatDB vs. HarperDB vs. Heroic

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Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

Application development environment with integrated database management system

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Primary database model

Relational DBMS

Document store
Key-value store

Document store

Time Series DBMS

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Website

www.4d.com

www.harperdb.io

github.com/spotify/heroic

Technical documentation

developer.4d.com

docs.harperdb.io/docs

spotify.github.io/heroic

Developer

4D, Inc

FatCloud

HarperDB

Spotify

Initial release

1984

2012

2017

2014

Current release

v20, April 2023

3.1, August 2021

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache 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

Node.js

Java

Server operating systems

OS X
Windows

Windows

Linux
OS X

Data scheme

yes

schema-free

dynamic schema

schema-free

Typing

predefined data types such as float or date

yes

JSON data types

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

via Elasticsearch

SQL

Support of SQL

yes

close to SQL 92

Via inetgration in SQL Server

SQL-like data manipulation statements

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

HQL (Heroic Query Language, a JSON-based language)
HTTP API

Supported programming languages

4D proprietary IDE
PHP

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

Server-side scripts

Stored procedures

yes

via applications

Custom Functions

since release 3.1

Triggers

yes

via applications

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

A table resides as a whole on one (or more) nodes in a cluster

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

selectable replication factor

yes

the nodes on which a table resides can be defined

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Eventual 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

yes, using LMDB

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

Can implement custom security layer via applications

Access rights for users and roles

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More resources

DB-Engines blog posts

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

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