DBMS > Percona Server for MongoDB vs. Riak KV vs. RisingWave vs. Sadas Engine

System Properties Comparison Percona Server for MongoDB vs. Riak KV vs. RisingWave vs. Sadas Engine

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Editorial information provided by DB-Engines

Name

Description

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

Distributed, fault tolerant key-value store

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

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Document store

Key-value store

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

Relational DBMS

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

Score	0.52
Rank	#254	Overall
	#39	Document stores

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

Score	0.58
Rank	#242	Overall
	#111	Relational DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Website

www.percona.com/mongodb/software/percona-server-for-mongodb

www.risingwave.com/database

www.sadasengine.com

Technical documentation

docs.percona.com/percona-distribution-for-mongodb

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

docs.risingwave.com/docs/current/intro

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Percona

OpenSource, formerly Basho Technologies

RisingWave Labs

SADAS s.r.l.

Initial release

2015

2009

2022

2006

Current release

3.4.10-2.10, November 2017

3.2.0, December 2022

1.2, September 2023

8.0

License

Commercial or Open Source

Open Source

GPL Version 2

Open Source

Apache version 2, commercial enterprise edition

Open Source

Apache Version 2.0

commercial

free trial version available

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++

Erlang

Rust

C++

Server operating systems

Linux

Linux
OS X

Docker
Linux
macOS

AIX
Linux
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

Standard SQL-types and JSON

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.

Secondary indexes

yes

restricted

yes

SQL

Support of SQL

yes

APIs and other access methods

proprietary protocol using JSON

HTTP API
Native Erlang Interface

JDBC
PostgreSQL wire protocol

JDBC
ODBC
Proprietary protocol

Supported programming languages

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

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

Go
Java
JavaScript (Node.js)
Python

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

JavaScript

Erlang

UDFs in Python or Java

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

none

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

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

links between data sets can be stored

yes

Transaction concepts

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

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

via In-Memory Engine

yes

managed by 'Learn by Usage'

User concepts

Access control

Access rights for users and roles

yes, using Riak Security

Users and Roles

Access rights for users, groups and roles according to SQL-standard

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