DBMS > DuckDB vs. MySQL vs. PouchDB vs. Sqrrl vs. Transbase

System Properties Comparison DuckDB vs. MySQL vs. PouchDB vs. Sqrrl vs. Transbase

Editorial information provided by DB-Engines

Name

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.

Description

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

Widely used open source RDBMS

JavaScript DBMS with an API inspired by CouchDB

Adaptable, secure NoSQL built on Apache Accumulo

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Relational DBMS

Key/Value like access via memcached API

Document store

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	4.57
Rank	#74	Overall
	#40	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

duckdb.org

www.mysql.com

pouchdb.com

sqrrl.com

www.transaction.de/en/products/transbase.html

Technical documentation

duckdb.org/docs

dev.mysql.com/doc

pouchdb.com/guides

www.transaction.de/en/products/transbase/features.html

Developer

Oracle

since 2010, originally MySQL AB, then Sun

Apache Software Foundation

Amazon

originally Sqrrl Data, Inc.

Transaction Software GmbH

Initial release

2018

1995

2012

1987

Current release

0.10, February 2024

8.4.0, April 2024

7.1.1, June 2019

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

MIT License

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

commercial

free development license

Cloud-based only

Only available as a cloud service

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Implementation language

C++

C and C++

JavaScript

Java

C and C++

Server operating systems

server-less

FreeBSD
Linux
OS X
Solaris
Windows

server-less, requires a JavaScript environment (browser, Node.js)

Linux

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

schema-free

yes

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

Secondary indexes

yes

via views

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

APIs and other access methods

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP REST

only for PouchDB Server
JavaScript API

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

JavaScript

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

yes

proprietary syntax

View functions in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

with a proxy-based framework, named couchdb-lounge

Sharding

making use of Hadoop

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

selectable replication factor

making use of Hadoop

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

Eventual Consistency

Immediate Consistency

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

Atomic updates per row, document, or graph entity

yes

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

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 with fine-grained authorization concept

no user groups or roles

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

fine grained access rights according to SQL-standard

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