DBMS > Bangdb vs. Drizzle vs. FatDB vs. TerarkDB vs. TimescaleDB

System Properties Comparison Bangdb vs. Drizzle vs. FatDB vs. TerarkDB vs. TimescaleDB

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.

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the 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.

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Document store
Key-value store

Key-value store

Time Series DBMS

Secondary database models

Spatial 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	0.08
Rank	#367	Overall
	#56	Key-value stores

Score	4.46
Rank	#71	Overall
	#5	Time Series DBMS

Website

bangdb.com

github.com/bytedance/terarkdb

www.timescale.com

Technical documentation

docs.bangdb.com

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

docs.timescale.com

Developer

Sachin Sinha, BangDB

Drizzle project, originally started by Brian Aker

FatCloud

ByteDance, originally Terark

Timescale

Initial release

2012

2008

2012

2016

2017

Current release

BangDB 2.0, October 2021

7.2.4, September 2012

2.15.0, May 2024

License

Commercial or Open Source

Open Source

BSD 3

Open Source

GNU GPL

commercial

restricted open source version available

Open Source

Apache 2.0

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++

Server operating systems

Linux

FreeBSD
Linux
OS X

Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

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

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

yes

with proprietary extensions

Via inetgration in SQL Server

yes

full PostgreSQL SQL syntax

APIs and other access methods

Proprietary protocol
RESTful HTTP API

JDBC

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

C++ API
Java API

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

Supported programming languages

C
C#
C++
Java
Python

C
C++
Java
PHP

C++
Java

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

via applications

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes, Notifications (with Streaming only)

hooks for callbacks inside the server can be used.

yes

via applications

yes

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

yes, across time and space (hash partitioning) attributes

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

selectable replication factor

none

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

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, optimistic concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) 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

User concepts

Access control

yes (enterprise version only)

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Can implement custom security layer via applications

fine grained access rights according to SQL-standard

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More resources

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Recent citations in the news

TimescaleDB Is a Vector Database Now, Too
25 September 2023, Datanami

Timescale Acquires PopSQL to Bring a Modern, Collaborative SQL GUI to PostgreSQL Developers
4 April 2024, PR Newswire

Power IoT and time-series workloads with TimescaleDB for Azure Database for PostgreSQL
18 March 2019, Microsoft

Timescale Valuation Rockets to Over $1B with $110M Round, Marking the Explosive Rise of Time-Series Data
22 February 2022, businesswire.com

TimescaleDB goes distributed; implements ‘Chunking’ over ‘Sharding’ for scaling-out
22 August 2019, Packt Hub

provided by Google News

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