DBMS > Brytlyt vs. Couchbase vs. mSQL vs. Percona Server for MongoDB vs. Percona Server for MySQL

System Properties Comparison Brytlyt vs. Couchbase vs. mSQL vs. Percona Server for MongoDB vs. Percona Server for MySQL

Editorial information provided by DB-Engines

Name

Description

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

mSQL (Mini SQL) is a simple and lightweight RDBMS

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

Enhanced drop-in replacement for MySQL based on XtraDB or TokuDB storage engines with improved performance and additional diagnostic and management features.

Primary database model

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

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

Score	0.29
Rank	#288	Overall
	#131	Relational DBMS

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	0.52
Rank	#254	Overall
	#39	Document stores

Score	2.03
Rank	#122	Overall
	#57	Relational DBMS

Website

brytlyt.io

www.couchbase.com

hughestech.com.au/products/msql

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

www.percona.com/software/mysql-database/percona-server

Technical documentation

docs.brytlyt.io

docs.couchbase.com

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

www.percona.com/downloads/Percona-Server-LATEST

Developer

Brytlyt

Couchbase, Inc.

Hughes Technologies

Percona

Initial release

2016

2011

1994

2015

2008

Current release

5.0, August 2023

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

4.4, October 2021

3.4.10-2.10, November 2017

8.0.36-28, 2024

License

Commercial or Open Source

commercial

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

commercial

free licenses can be provided

Open Source

GPL Version 2

Open Source

GPL version 2

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, C++ and CUDA

C, C++, Go and Erlang

C++

C and C++

Server operating systems

Linux
OS X
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux

Data scheme

yes

schema-free

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

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

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

yes

APIs and other access methods

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

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

JDBC
ODBC

proprietary protocol using JSON

ADO.NET
JDBC
ODBC

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

C
C++
Delphi
Java
Perl
PHP
Tcl

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

Ada
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

JavaScript

yes

Triggers

yes

via the TAP protocol

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

including cross data center replication
Source-replica replication

none

Source-replica replication

Multi-source replication
Source-replica replication
XtraDB Cluster

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

selectable on a per-operation basis

none

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

Ephemeral buckets

yes

via In-Memory Engine

yes

User concepts

Access control

fine grained access rights according to SQL-standard

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

Access rights for users and roles

Users with fine-grained authorization concept

no user groups or roles

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