DBMS > Apache IoTDB vs. jBASE vs. RRDtool vs. Vitess

System Properties Comparison Apache IoTDB vs. jBASE vs. RRDtool vs. Vitess

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Editorial information provided by DB-Engines

Name

Description

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

A robust multi-value DBMS comprising development tools and middleware

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.

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	1.41
Rank	#159	Overall
	#3	Multivalue DBMS

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Score	0.82
Rank	#209	Overall
	#97	Relational DBMS

Website

iotdb.apache.org

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

oss.oetiker.ch/rrdtool

vitess.io

Technical documentation

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

oss.oetiker.ch/rrdtool/doc

vitess.io/docs

Developer

Apache Software Foundation

Rocket Software (formerly Zumasys)

Tobias Oetiker

The Linux Foundation, PlanetScale

Initial release

2018

1991

1999

2013

Current release

1.1.0, April 2023

5.7

1.8.0, 2022

15.0.2, December 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

GPL V2 and FLOSS

Open Source

Apache Version 2.0, commercial licenses 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

Java

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

Server operating systems

All OS with a Java VM (>= 1.8)

AIX
Linux
Windows

HP-UX
Linux

Docker
Linux
macOS

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

optional

Numeric data only

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.

yes

Exporting into and restoring from XML files possible

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

Embedded SQL for jBASE in BASIC

yes

with proprietary extensions

APIs and other access methods

JDBC
Native API

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

in-process shared library
Pipes

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

.Net
Basic
Jabbascript
Java

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

yes

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

none

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

by using the rrdcached daemon

yes

table locks or row locks depending on storage engine

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

yes

Access rights can be defined down to the item level

Users with fine-grained authorization concept

no user groups or roles

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More resources

DB-Engines blog posts

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