DBMS > IRONdb vs. Quasardb vs. STSdb vs. TerarkDB

System Properties Comparison IRONdb vs. Quasardb vs. STSdb vs. TerarkDB

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Editorial information provided by DB-Engines

Name

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

Description

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

Distributed, high-performance timeseries database

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Time Series DBMS

Key-value store

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

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

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

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

www.circonus.com/solutions/time-series-database/

quasar.ai

github.com/STSSoft/STSdb4

github.com/bytedance/terarkdb

Technical documentation

docs.circonus.com/irondb/category/getting-started

doc.quasar.ai/master

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Circonus LLC.

quasardb

STS Soft SC

ByteDance, originally Terark

Initial release

2017

2009

2011

2016

Current release

V0.10.20, January 2018

3.14.1, January 2024

4.0.8, September 2015

License

Commercial or Open Source

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

GPLv2, commercial license available

commercial

restricted open source version 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

C and C++

C++

Server operating systems

Linux

BSD
Linux
OS X
Windows

Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

text, numeric, histograms

yes

integer and binary

yes

primitive types and user defined types (classes)

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

with tags

SQL

Support of SQL

SQL-like query language (Circonus Analytics Query Language: CAQL)

SQL-like query language

APIs and other access methods

HTTP API

.NET Client API

C++ API
Java API

Supported programming languages

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

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

C#
Java

C++
Java

Server-side scripts

Stored procedures

yes, in Lua

Triggers

Partitioning methods

Methods for storing different data on different nodes

Automatic, metric affinity per node

Sharding

consistent hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

configurable replication factor, datacenter aware

Source-replica replication with selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Transient mode

yes

User concepts

Access control

Cryptographically strong user authentication and audit trail

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