DBMS > Brytlyt vs. JaguarDB vs. MySQL vs. Tibero vs. Trafodion

System Properties Comparison Brytlyt vs. JaguarDB vs. MySQL vs. Tibero vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

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

Performant, highly scalable DBMS for AI and IoT applications

Widely used open source RDBMS

A secure RDBMS, designed for easy portability from Oracle

Transactional SQL-on-Hadoop DBMS

Primary database model

Relational DBMS

Key-value store
Vector DBMS

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.38
Rank	#276	Overall
	#127	Relational DBMS

Score	0.06
Rank	#381	Overall
	#59	Key-value stores
	#15	Vector DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	1.59
Rank	#148	Overall
	#68	Relational DBMS

Website

brytlyt.io

www.jaguardb.com

www.mysql.com

us.tmaxsoft.com/products/tibero

trafodion.apache.org

Technical documentation

docs.brytlyt.io

www.jaguardb.com/support.html

dev.mysql.com/doc

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

trafodion.apache.org/documentation.html

Developer

Brytlyt

DataJaguar, Inc.

Oracle

since 2010, originally MySQL AB, then Sun

TmaxSoft

Apache Software Foundation, originally developed by HP

Initial release

2016

2015

1995

2003

2014

Current release

5.0, August 2023

3.3 July 2023

8.4.0, April 2024

6, April 2015

2.3.0, February 2019

License

Commercial or Open Source

commercial

Open Source

GPL V3.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++ and CUDA

C++

the server part. Clients available in other languages

C and C++

C and Assembler

C++, Java

Server operating systems

Linux
OS X
Windows

Linux

FreeBSD
Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Windows

Linux

Data scheme

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

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

with proprietary extensions

yes

APIs and other access methods

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

JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

ADO.NET
JDBC
ODBC

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

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

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

yes

proprietary syntax

Persistent Stored Procedure (PSM)

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

horizontal partitioning

by range, hash, list or composite

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

Multi-source replication
Source-replica replication

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

planned for next version

User concepts

Access control

fine grained access rights according to SQL-standard

rights management via user accounts

Users with fine-grained authorization concept

no user groups or roles

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

fine grained access rights according to SQL-standard

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