DBMS > Riak KV vs. STSdb vs. TDengine vs. ToroDB vs. Yanza

System Properties Comparison Riak KV vs. STSdb vs. TDengine vs. ToroDB vs. Yanza

Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Distributed, fault tolerant key-value store

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Time Series DBMS and big data platform

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Time Series DBMS for IoT Applications

Primary database model

Key-value store

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

Secondary database models

Relational DBMS

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

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

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

Score	2.60
Rank	#107	Overall
	#8	Time Series DBMS

Website

github.com/STSSoft/STSdb4

github.com/taosdata/TDengine
tdengine.com

github.com/torodb/server

yanza.com

Technical documentation

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

docs.tdengine.com

Developer

OpenSource, formerly Basho Technologies

STS Soft SC

TDEngine, previously Taos Data

8Kdata

Yanza

Initial release

2009

2011

2019

2016

2015

Current release

3.2.0, December 2022

4.0.8, September 2015

3.0, August 2022

License

Commercial or Open Source

Open Source

Apache version 2, commercial enterprise edition

Open Source

GPLv2, commercial license available

Open Source

AGPL V3, also commercial editions available

Open Source

AGPL-V3

commercial

free version available

Cloud-based only

Only available as a cloud service

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Erlang

Java

Server operating systems

Linux
OS X

Windows

Linux
Windows

All OS with a Java 7 VM

Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

yes

string, integer, double, boolean, date, object_id

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

restricted

SQL

Support of SQL

Standard SQL with extensions for time-series applications

APIs and other access methods

HTTP API
Native Erlang Interface

.NET Client API

JDBC
RESTful HTTP API

HTTP API

Supported programming languages

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++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust

any language that supports HTTP calls

Server-side scripts

Stored procedures

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

yes, via alarm monitoring

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

yes

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

links between data sets can be stored

Transaction concepts

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

User concepts

Access control

yes, using Riak Security

yes

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

TDengine™ is a next generation data historian purpose-built for Industry 4.0 and...
» more

Competitive advantages

High Performance at any Scale: TDengine is purpose-built for handling massive industrial...
» more

Typical application scenarios

TDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
» more

Market metrics

TDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
» more

Licensing and pricing models

TDengine OSS is an open source, cloud native time series database. It includes built-in...
» more

News

Can Typical Time-Series Databases Replace Data Historians?
8 May 2024

TDengine 3.3.0.0 Release Notes
7 May 2024

How to Unlock Value from Industrial Data with AI and ML Technology
6 May 2024

Compare InfluxDB vs. TDengine
19 April 2024

Why We Need the Next Generation Data Historian
15 April 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

Recent citations in the news

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

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

A Critique of Resizable Hash Tables: Riak Core & Random Slicing
26 August 2018, InfoQ.com

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

TDengine debuts cloud-based time-series data processing platform for IoT deployments
20 September 2022, SiliconANGLE News

New TDengine Benchmark Results Show Up to 37.0x Higher Query Performance Than InfluxDB and TimescaleDB
28 February 2023, GlobeNewswire

Comparing Different Time-Series Databases
10 February 2022, hackernoon.com

provided by Google News

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