DBMS > Alibaba Cloud Table Store vs. IRONdb vs. OpenTSDB vs. OrigoDB

System Properties Comparison Alibaba Cloud Table Store vs. IRONdb vs. OpenTSDB vs. OrigoDB

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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 fully managed Wide Column Store for large quantities of semi-structured data with real-time access

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

Scalable Time Series DBMS based on HBase

A fully ACID in-memory object graph database

Primary database model

Wide column store

Time Series DBMS

Document store
Object oriented DBMS

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

Score	0.25
Rank	#294	Overall
	#12	Wide column stores

Score	1.59
Rank	#140	Overall
	#12	Time Series DBMS

Score	0.00
Rank	#385	Overall
	#54	Document stores
	#21	Object oriented DBMS

Website

www.alibabacloud.com/product/table-store

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

opentsdb.net

origodb.com

Technical documentation

www.alibabacloud.com/help/en/tablestore

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

opentsdb.net/docs/build/html/index.html

origodb.com/docs

Developer

Alibaba

Circonus LLC.

currently maintained by Yahoo and other contributors

Robert Friberg et al

Initial release

2016

2017

2011

2009

under the name LiveDB

Current release

V0.10.20, January 2018

License

Commercial or Open Source

commercial

Open Source

LGPL

Open Source

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

C and C++

Java

Server operating systems

hosted

Linux

Linux
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

text, numeric, histograms

numeric data for metrics, strings for tags

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

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

APIs and other access methods

HTTP API

HTTP API
Telnet API

.NET Client API
HTTP API
LINQ

Supported programming languages

Java
Python

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

Erlang
Go
Java
Python
R
Ruby

.Net

Server-side scripts

Stored procedures

yes, in Lua

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Automatic, metric affinity per node

Sharding

based on HBase

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

configurable replication factor, datacenter aware

selectable replication factor

based on HBase

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

depending on model

Transaction concepts

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

Atomic single-row operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

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

Role based authorization

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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

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