DBMS > FatDB vs. HarperDB vs. PostgreSQL vs. RisingWave

System Properties Comparison FatDB vs. HarperDB vs. PostgreSQL vs. RisingWave

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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

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.

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

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

Primary database model

Document store
Key-value store

Document store

Relational DBMS

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Relational DBMS

Secondary database models

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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

Score	0.60
Rank	#244	Overall
	#38	Document stores

Score	636.25
Rank	#4	Overall
	#4	Relational DBMS

Score	0.64
Rank	#238	Overall
	#110	Relational DBMS

Website

www.harperdb.io

www.postgresql.org

www.risingwave.com/database

Technical documentation

docs.harperdb.io/docs

www.postgresql.org/docs

docs.risingwave.com/docs/current/intro

Developer

FatCloud

HarperDB

PostgreSQL Global Development Group

www.postgresql.org/developer

RisingWave Labs

Initial release

2012

2017

1989

1989: Postgres, 1996: PostgreSQL

2022

Current release

3.1, August 2021

16.3, May 2024

1.2, September 2023

License

Commercial or Open Source

commercial

free community edition available

Open Source

BSD

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.

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Implementation language

Node.js

Rust

Server operating systems

Windows

Linux
OS X

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

Docker
Linux
macOS

Data scheme

schema-free

dynamic schema

yes

Typing

predefined data types such as float or date

yes

JSON data types

yes

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

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

Via inetgration in SQL Server

SQL-like data manipulation statements

yes

standard with numerous extensions

yes

APIs and other access methods

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

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JDBC
PostgreSQL wire protocol

Supported programming languages

.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

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

via applications

Custom Functions

since release 3.1

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

UDFs in Python or Java

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

partitioning by range, list and (since PostgreSQL 11) by hash

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

the nodes on which a table resides can be defined

Source-replica replication

other methods possible by using 3rd party extensions

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

ACID

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

Can implement custom security layer via applications

Access rights for users and roles

fine grained access rights according to SQL-standard

Users and Roles

More information provided by the system vendor

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