DBMS > Apache Drill vs. Hypertable vs. IRONdb vs. SWC-DB

System Properties Comparison Apache Drill vs. Hypertable vs. IRONdb vs. SWC-DB

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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.

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

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

A high performance, scalable Wide Column DBMS

Primary database model

Document store
Relational DBMS

Wide column store

Time Series DBMS

Wide column store

Secondary database models

Time Series DBMS

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

Score	1.95
Rank	#127	Overall
	#23	Document stores
	#60	Relational DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

drill.apache.org

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

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

drill.apache.org/docs

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

Developer

Apache Software Foundation

Hypertable Inc.

Circonus LLC.

Alex Kashirin

Initial release

2012

2009

2017

2020

Current release

1.20.3, January 2023

0.9.8.11, March 2016

V0.10.20, January 2018

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

GNU version 3. Commercial license available

commercial

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C and C++

C++

Server operating systems

Linux
OS X
Windows

an inofficial Windows port is available

Linux

Data scheme

schema-free

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

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

SQL-like query language

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

C++ API
Thrift

HTTP API

Proprietary protocol
Thrift

Supported programming languages

C++

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

C++

Server-side scripts

Stored procedures

user defined functions

yes, in Lua

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic, metric affinity per node

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor on file system level

configurable replication factor, datacenter aware

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

In-memory capabilities

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

Depending on the underlying data source

User concepts

Access control

Depending on the underlying data source

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