DBMS > Apache IoTDB vs. EsgynDB vs. IRONdb vs. OpenTSDB vs. Transwarp StellarDB

System Properties Comparison Apache IoTDB vs. EsgynDB vs. IRONdb vs. OpenTSDB vs. Transwarp StellarDB

Editorial information provided by DB-Engines

Name

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

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

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

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

Scalable Time Series DBMS based on HBase

A distributed graph DBMS built for enterprise-level graph applications

Primary database model

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

Score	1.31
Rank	#164	Overall
	#14	Time Series DBMS

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	1.68
Rank	#142	Overall
	#12	Time Series DBMS

Score	0.07
Rank	#371	Overall
	#39	Graph DBMS

Website

iotdb.apache.org

www.esgyn.cn

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

opentsdb.net

www.transwarp.cn/en/product/stellardb

Technical documentation

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

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

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

Developer

Apache Software Foundation

Esgyn

Circonus LLC.

currently maintained by Yahoo and other contributors

Transwarp

Initial release

2018

2015

2017

2011

Current release

1.1.0, April 2023

V0.10.20, January 2018

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

LGPL

commercial

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

C++, Java

C and C++

Java

Server operating systems

All OS with a Java VM (>= 1.8)

Linux

Linux
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

text, numeric, histograms

numeric data for metrics, strings for tags

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

SQL

Support of SQL

SQL-like query language

yes

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

SQL-like query language

APIs and other access methods

JDBC
Native API

ADO.NET
JDBC
ODBC

HTTP API

HTTP API
Telnet API

OpenCypher

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

All languages supporting JDBC/ODBC/ADO.Net

.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

Server-side scripts

Stored procedures

yes

Java Stored Procedures

yes, in Lua

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

Automatic, metric affinity per node

Sharding

based on HBase

horizontal partitioning

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

Multi-source replication between multi datacenters

configurable replication factor, datacenter aware

selectable replication factor

based on HBase

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

Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

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

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

fine grained access rights according to SQL-standard

yes

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

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

show all

Recent citations in the news

AMD EPYC 4364P & 4564P @ DDR5-4800 / DDR5-5200 vs. Intel Xeon E-2488 Review
6 June 2024, Phoronix

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

Apache Promotes IoT Database Project
25 September 2020, Datanami

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

provided by Google News

Application observability firm Apica buys telemetry data startup Circonus and adds more funding
21 February 2024, SiliconANGLE News

Apica Acquires Telemetry Data Management Pioneer Circonus And Lands New Funding
22 February 2024, Datanami

Apica gets $6 million in funding and buys Circonus -
21 February 2024, Enterprise Times

provided by Google News

Pinterest Switches from OpenTSDB to Their Own Time Series Database
16 September 2018, InfoQ.com

Brain Monitoring with Kafka, OpenTSDB, and Grafana
5 August 2016, KDnuggets

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

MapR to help admins peer into dense Hadoop clusters
28 June 2016, SiliconANGLE News

LogicMonitor Rolls a Time Series Database for Finer-Grain Reporting
1 June 2016, The New Stack

provided by Google News

Share this page