DBMS > Alibaba Cloud Table Store vs. BaseX vs. RRDtool vs. SwayDB

System Properties Comparison Alibaba Cloud Table Store vs. BaseX vs. RRDtool vs. SwayDB

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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

Light-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.

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.

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

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

Score	0.31
Rank	#297	Overall
	#11	Wide column stores

Score	1.84
Rank	#135	Overall
	#4	Native XML DBMS

Score	1.90
Rank	#132	Overall
	#11	Time Series DBMS

Score	0.04
Rank	#387	Overall
	#61	Key-value stores

Website

www.alibabacloud.com/product/table-store

basex.org

oss.oetiker.ch/rrdtool

swaydb.simer.au

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.basex.org

oss.oetiker.ch/rrdtool/doc

Developer

Alibaba

BaseX GmbH

Tobias Oetiker

Simer Plaha

Initial release

2016

2007

1999

2018

Current release

11.0, June 2024

1.8.0, 2022

License

Commercial or Open Source

commercial

Open Source

BSD license

Open Source

GPL V2 and FLOSS

Open Source

GNU Affero GPL V3.0

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

Java

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

Scala

Server operating systems

hosted

Linux
OS X
Windows

HP-UX
Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

XQuery supports types

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

SQL

Support of SQL

APIs and other access methods

HTTP API

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

in-process shared library
Pipes

Supported programming languages

Java
Python

Actionscript
C
C#
Haskell
Java
JavaScript

Node.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic

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

Java
Kotlin
Scala

Server-side scripts

Stored procedures

yes

Triggers

yes

via events

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

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

Transaction concepts

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

Atomic single-row operations

multiple readers, single writer

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

by using the rrdcached daemon

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

Access rights based on subaccounts and tokens

Users with fine-grained authorization concept on 4 levels

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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

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