DBMS > Hypertable vs. IRONdb vs. Trafodion vs. Yanza

System Properties Comparison Hypertable vs. IRONdb vs. Trafodion vs. Yanza

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Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

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

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

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

Description

An open source BigTable implementation based on distributed file systems such as Hadoop

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

Transactional SQL-on-Hadoop DBMS

Time Series DBMS for IoT Applications

Primary database model

Website

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

trafodion.apache.org

yanza.com

Technical documentation

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

trafodion.apache.org/documentation.html

Developer

Hypertable Inc.

Circonus LLC.

Apache Software Foundation, originally developed by HP

Yanza

Initial release

2009

2017

2014

2015

Current release

0.9.8.11, March 2016

V0.10.20, January 2018

2.3.0, February 2019

License

Commercial or Open Source

Open Source

GNU version 3. Commercial license available

commercial

Open Source

Apache 2.0

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

C++

C and C++

C++, Java

Server operating systems

Linux
OS X
Windows

an inofficial Windows port is available

Linux

Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

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

yes

APIs and other access methods

C++ API
Thrift

HTTP API

ADO.NET
JDBC
ODBC

HTTP API

Supported programming languages

C++
Java
Perl
PHP
Python
Ruby

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

All languages supporting JDBC/ODBC/ADO.Net

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes, in Lua

Java Stored Procedures

Triggers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic, metric affinity per node

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor on file system level

configurable replication factor, datacenter aware

yes, via HBase

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

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.

User concepts

Access control

fine grained access rights according to SQL-standard

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