DBMS > Databend vs. Microsoft Azure Table Storage vs. RRDtool vs. SQLite vs. Transwarp KunDB

System Properties Comparison Databend vs. Microsoft Azure Table Storage vs. RRDtool vs. SQLite vs. Transwarp KunDB

Editorial information provided by DB-Engines

Name

Description

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

A Wide Column Store for rapid development using massive semi-structured datasets

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.

Widely used embeddable, in-process RDBMS

OLTP DBMS based on a distributed architecture and highly compatible with MySQL and Oracle

Primary database model

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

Score	0.30
Rank	#287	Overall
	#130	Relational DBMS

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	0.10
Rank	#344	Overall
	#151	Relational DBMS

Website

github.com/datafuselabs/databend
www.databend.com

azure.microsoft.com/en-us/services/storage/tables

oss.oetiker.ch/rrdtool

www.sqlite.org

www.transwarp.cn/en/product/kundb

Technical documentation

docs.databend.com

oss.oetiker.ch/rrdtool/doc

www.sqlite.org/docs.html

Developer

Databend Labs

Microsoft

Tobias Oetiker

Dwayne Richard Hipp

Transwarp

Initial release

2021

2012

1999

2000

Current release

1.0.59, April 2023

1.8.0, 2022

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

GPL V2 and FLOSS

Open Source

Public Domain

commercial

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

Rust

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

Server operating systems

hosted
Linux
macOS

hosted

HP-UX
Linux

server-less

Data scheme

yes

schema-free

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

Numeric data only

yes

not rigid because of 'dynamic typing' concept.

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.

Exporting into and restoring from XML files possible

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-92 is not fully supported

yes

APIs and other access methods

CLI Client
JDBC
RESTful HTTP API

RESTful HTTP API

in-process shared library
Pipes

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
Rust

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

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

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

by using the rrdcached daemon

yes

via file-system locks

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

User concepts

Access control

Users with fine-grained authorization concept, user roles

Access rights based on private key authentication or shared access signatures

yes

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