DBMS > Amazon Redshift vs. DuckDB vs. Hazelcast vs. Percona Server for MongoDB vs. SWC-DB

System Properties Comparison Amazon Redshift vs. DuckDB vs. Hazelcast vs. Percona Server for MongoDB vs. SWC-DB

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

An embeddable, in-process, column-oriented SQL OLAP RDBMS

A widely adopted in-memory data grid

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

A high performance, scalable Wide Column DBMS

Primary database model

Secondary database models

Document store

JSON support with IMDG 3.12

Time Series DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	4.63
Rank	#69	Overall
	#37	Relational DBMS

Score	5.46
Rank	#61	Overall
	#7	Key-value stores

Score	0.60
Rank	#246	Overall
	#39	Document stores

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Website

aws.amazon.com/redshift

duckdb.org

hazelcast.com

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

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

docs.aws.amazon.com/redshift

duckdb.org/docs

hazelcast.org/imdg/docs

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

Developer

Amazon (based on PostgreSQL)

Hazelcast

Percona

Alex Kashirin

Initial release

2012

2018

2008

2015

2020

Current release

0.10, February 2024

5.3.6, November 2023

3.4.10-2.10, November 2017

0.5, April 2021

License

Commercial or Open Source

commercial

Open Source

MIT License

Open Source

Apache Version 2; commercial licenses available

Open Source

GPL Version 2

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Java

C++

Server operating systems

hosted

server-less

All OS with a Java VM

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

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

the object must implement a serialization strategy

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

SQL-like query language

APIs and other access methods

JDBC
ODBC

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

JCache
JPA
Memcached protocol
RESTful HTTP API

proprietary protocol using JSON

Proprietary protocol
Thrift

Supported programming languages

All languages supporting JDBC/ODBC

C
C#

3rd party driver
C++
Crystal

3rd party driver
Go

3rd party driver
Java
Lisp

3rd party driver
Python
R
Ruby

3rd party driver
Rust
Swift
Zig

3rd party driver

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

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

C++

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Event Listeners, Executor Services

JavaScript

Triggers

yes

Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes

Replicated Map

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

Transaction concepts

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

ACID

one or two-phase-commit; repeatable reads; read commited

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

User concepts

Access control

fine grained access rights according to SQL-standard

Role-based access control

Access rights for users and roles

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