DBMS > Apache Drill vs. IRONdb vs. OpenTSDB vs. Spark SQL

System Properties Comparison Apache Drill vs. IRONdb vs. OpenTSDB vs. Spark SQL

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Editorial information provided by DB-Engines

Name

Description

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

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

Scalable Time Series DBMS based on HBase

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Document store
Relational DBMS

Time Series DBMS

Relational DBMS

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

Score	2.89
Rank	#106	Overall
	#20	Document stores
	#55	Relational DBMS

Score	0.00
Rank	#354	Overall
	#33	Time Series DBMS

Score	1.84
Rank	#130	Overall
	#8	Time Series DBMS

Score	22.86
Rank	#35	Overall
	#21	Relational DBMS

Website

drill.apache.org

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

opentsdb.net

spark.apache.org/sql

Technical documentation

drill.apache.org/docs

docs.circonus.com/irondb

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

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Apache Software Foundation

Circonus LLC.

currently maintained by Yahoo and other contributors

Apache Software Foundation

Initial release

2012

2017

2011

2014

Current release

1.19.0, June 2021

V0.10.20, January 2018

3.2.0, October 2021

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

LGPL

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C and C++

Java

Scala

Server operating systems

Linux
OS X
Windows

Linux

Linux
Windows

Linux
OS X
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

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

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

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

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

HTTP API

HTTP API
Telnet API

JDBC
ODBC

Supported programming languages

C++

.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

Java
Python
R
Scala

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

based on HBase

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

configurable replication factor, datacenter aware

selectable replication factor

based on HBase

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

based on HBase

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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