DBMS > Brytlyt vs. MonetDB vs. MySQL vs. Sphinx vs. TDengine

System Properties Comparison Brytlyt vs. MonetDB vs. MySQL vs. Sphinx vs. TDengine

Editorial information provided by DB-Engines

Name

Description

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

A relational database management system that stores data in columns

Widely used open source RDBMS

Open source search engine for searching in data from different sources, e.g. relational databases

Time Series DBMS and big data platform

Primary database model

Relational DBMS

Key/Value like access via memcached API

Search engine

Time Series DBMS

Secondary database models

Document store
Spatial DBMS

Relational DBMS

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

Score	0.38
Rank	#276	Overall
	#127	Relational DBMS

Score	1.72
Rank	#141	Overall
	#64	Relational DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	5.95
Rank	#55	Overall
	#5	Search engines

Score	2.68
Rank	#106	Overall
	#9	Time Series DBMS

Website

github.com/taosdata/TDengine
tdengine.com

Technical documentation

docs.brytlyt.io

www.monetdb.org/Documentation

dev.mysql.com/doc

sphinxsearch.com/docs

docs.tdengine.com

Developer

Brytlyt

MonetDB BV

Oracle

since 2010, originally MySQL AB, then Sun

Sphinx Technologies Inc.

TDEngine, previously Taos Data

Initial release

2016

2004

1995

2001

2019

Current release

5.0, August 2023

Dec2023 (11.49), December 2023

8.4.0, April 2024

3.5.1, February 2023

3.0, August 2022

License

Commercial or Open Source

commercial

Open Source

Mozilla Public License 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

GPL version 2, commercial licence available

Open Source

AGPL V3, also commercial editions available

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 and C++

C++

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
OS X
Solaris
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux
Windows

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

full-text index on all search fields

SQL

Support of SQL

yes

SQL 2003 with some extensions

yes

with proprietary extensions

SQL-like query language (SphinxQL)

Standard SQL with extensions for time-series applications

APIs and other access methods

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

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Proprietary protocol

JDBC
RESTful HTTP API

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

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

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

yes, in SQL, C, R

yes

proprietary syntax

Triggers

yes

yes, via alarm monitoring

Partitioning methods

Methods for storing different data on different nodes

Sharding via remote tables

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Partitioning is done manually, search queries against distributed index is supported

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Source-replica replication available in experimental status

Multi-source replication
Source-replica replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

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

The original contents of fields are not stored in the Sphinx index.

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

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

yes

More information provided by the system vendor

Specific characteristics

TDengine™ is a next generation data historian purpose-built for Industry 4.0 and...
» more

Competitive advantages

High Performance at any Scale: TDengine is purpose-built for handling massive industrial...
» more

Typical application scenarios

TDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
» more

Market metrics

TDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
» more

Licensing and pricing models

TDengine OSS is an open source, cloud native time series database. It includes built-in...
» more

News

Mastering Memory Leak Detection in TDengine
31 May 2024

Seamless Data Integration from MQTT and InfluxDB to TDengine
22 May 2024

Solving Long Query Performance Bottlenecks
22 May 2024

What Is Predictive Maintenance?
17 May 2024

Can Typical Time-Series Databases Replace Data Historians?
8 May 2024

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