DBMS > Alibaba Cloud Table Store vs. Bangdb vs. RRDtool

System Properties Comparison Alibaba Cloud Table Store vs. Bangdb vs. RRDtool

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

A fully managed Wide Column Store for large quantities of semi-structured data with real-time access

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

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

Primary database model

Wide column store

Document store
Graph DBMS
Time Series DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

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

Score	0.26
Rank	#301	Overall
	#12	Wide column stores

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Website

www.alibabacloud.com/product/table-store

bangdb.com

oss.oetiker.ch/rrdtool

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.bangdb.com

oss.oetiker.ch/rrdtool/doc

Developer

Alibaba

Sachin Sinha, BangDB

Tobias Oetiker

Initial release

2016

2012

1999

Current release

BangDB 2.0, October 2021

1.8.0, 2022

License

Commercial or Open Source

commercial

Open Source

BSD 3

Open Source

GPL V2 and FLOSS

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C, C++

Implementations in Java (e.g. RRD4J) and C# available

Server operating systems

hosted

Linux

HP-UX
Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

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

Numeric data only

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.

Exporting into and restoring from XML files possible

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

SQL

Support of SQL

SQL like support with command line tool

APIs and other access methods

HTTP API

Proprietary protocol
RESTful HTTP API

in-process shared library
Pipes

Supported programming languages

Java
Python

C
C#
C++
Java
Python

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

Server-side scripts

Stored procedures

Triggers

yes, Notifications (with Streaming only)

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

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

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Tunable consistency, set CAP knob accordingly

none

Foreign keys

Referential integrity

Transaction concepts

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

Atomic single-row operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes

by using the rrdcached daemon

Durability

Support for making data persistent

yes

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

Access rights based on subaccounts and tokens

yes (enterprise version only)

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

show all

Recent citations in the news

Apache Software Foundation Announces New Top-Level Project Apache Paimon
19 April 2024, Datanami

Apache Software Foundation Announces New Top-Level Project Apache® Paimon
16 April 2024, Yahoo Finance

Gartner’s Magic Quadrant for Cloud Database Management Systems
9 December 2020, CRN

25 Best Cloud Service Providers (Public and Private) in 2024
4 June 2023, CybersecurityNews

Top data analytics tools comparison: Alibaba Cloud, AWS, Azure, Google Cloud, IBM
5 December 2019, Wire19

provided by Google News

SQLi vulnerability in Cacti could lead to RCE (CVE-2023-51448)
9 January 2024, Help Net Security

Critical IP spoofing bug patched in Cacti
15 December 2022, The Daily Swig

Cacti: Using Graphs to Monitor Networks and Devices
16 March 2011, Packt Hub

A plotting utility for text mode consoles and terminals @tenox77
28 June 2023, Adafruit Blog

How to install Cacti SNMP Monitor on Ubuntu
24 November 2017, TechRepublic

provided by Google News

Share this page