DBMS > Apache IoTDB vs. Riak KV vs. STSdb vs. Transbase

System Properties Comparison Apache IoTDB vs. Riak KV vs. STSdb vs. Transbase

Please select another system to include it in the comparison.

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

Distributed, fault tolerant key-value store

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Time Series DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Key-value store

Relational DBMS

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

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

iotdb.apache.org

github.com/STSSoft/STSdb4

www.transaction.de/en/products/transbase.html

Technical documentation

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

www.tiot.jp/riak-docs/riak/kv/latest

www.transaction.de/en/products/transbase/features.html

Developer

Apache Software Foundation

OpenSource, formerly Basho Technologies

STS Soft SC

Transaction Software GmbH

Initial release

2018

2009

2011

1987

Current release

1.1.0, April 2023

3.2.0, December 2022

4.0.8, September 2015

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache version 2, commercial enterprise edition

Open Source

GPLv2, commercial license available

commercial

free development license

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

Erlang

C and C++

Server operating systems

All OS with a Java VM (>= 1.8)

Linux
OS X

Windows

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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.

Secondary indexes

yes

restricted

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

JDBC
Native API

HTTP API
Native Erlang Interface

.NET Client API

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

C#
Java

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

yes

Erlang

yes

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

no "single point of failure"

none

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

selectable replication factor

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

links between data sets can be stored

yes

Transaction concepts

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

yes

Concurrency

Support for concurrent manipulation of data

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

yes

yes, using Riak Security

fine grained access rights according to SQL-standard

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

Recent citations in the news

TsFile: A Standard Format for IoT Time Series Data
27 February 2024, The New Stack

Linux 6.5 With AMD P-State EPP Default Brings Performance & Power Efficiency Benefits For Ryzen Servers
21 September 2023, Phoronix

AMD EPYC 8324P / 8324PN Siena 32-Core Siena Linux Server Performance Review
10 October 2023, Phoronix

Apache Promotes IoT Database Project
25 September 2020, Datanami

IoTDB Provides Data Management for Industrial Edge IT
15 October 2020, The New Stack

provided by Google News

Basho Revamps Riak Open-Source Database
22 September 2023, InformationWeek

Riak NoSQL Database: Use Cases and Best Practices
23 December 2011, InfoQ.com

Basho, Maker of Riak NoSQL Database, Raises $25M
13 January 2015, Data Center Knowledge

Riak NoSQL snapped up by Bet365
12 September 2017, ComputerWeekly.com

NoSQL pioneer Basho stamps its mark on time stamp data with Riak TS
6 October 2015, The Register

provided by Google News

Share this page