DBMS > Bangdb vs. Drizzle vs. Kinetica vs. RDF4J vs. TDengine

System Properties Comparison Bangdb vs. Drizzle vs. Kinetica vs. RDF4J vs. TDengine

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

Converged and high performance database for device data, events, time series, document and graph

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Fully vectorized database across both GPUs and CPUs

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Time Series DBMS and big data platform

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

RDF store

Time Series DBMS

Secondary database models

Spatial DBMS

Spatial DBMS
Time Series DBMS

Relational DBMS

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

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	2.68
Rank	#106	Overall
	#9	Time Series DBMS

Website

bangdb.com

www.kinetica.com

rdf4j.org

github.com/taosdata/TDengine
tdengine.com

Technical documentation

docs.bangdb.com

docs.kinetica.com

rdf4j.org/documentation

docs.tdengine.com

Developer

Sachin Sinha, BangDB

Drizzle project, originally started by Brian Aker

Kinetica

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

TDEngine, previously Taos Data

Initial release

2012

2008

2012

2004

2019

Current release

BangDB 2.0, October 2021

7.2.4, September 2012

7.1, August 2021

3.0, August 2022

License

Commercial or Open Source

Open Source

BSD 3

Open Source

GNU GPL

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

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

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

Implementation language

C, C++

C++

C, C++

Java

Server operating systems

Linux

FreeBSD
Linux
OS X

Linux

Linux
OS X
Unix
Windows

Linux
Windows

Data scheme

schema-free

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

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.

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

yes

with proprietary extensions

SQL-like DML and DDL statements

Standard SQL with extensions for time-series applications

APIs and other access methods

Proprietary protocol
RESTful HTTP API

JDBC

JDBC
ODBC
RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

JDBC
RESTful HTTP API

Supported programming languages

C
C#
C++
Java
Python

C
C++
Java
PHP

C++
Java
JavaScript (Node.js)
Python

Java
PHP
Python

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

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes, Notifications (with Streaming only)

hooks for callbacks inside the server can be used.

yes

triggers when inserted values for one or more columns fall within a specified range

yes

yes, via alarm monitoring

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

Multi-source replication
Source-replica 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

Tunable consistency, set CAP knob accordingly

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

in-memory storage is supported as well

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes, run db with in-memory only mode

yes

GPU vRAM or System RAM

User concepts

Access control

yes (enterprise version only)

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights for users and roles on table level

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

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22 May 2024

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