DBMS > Apache Drill vs. Graph Engine vs. IRONdb vs. OushuDB

System Properties Comparison Apache Drill vs. Graph Engine vs. IRONdb vs. OushuDB

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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

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

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

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

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

Primary database model

Document store
Relational DBMS

Graph DBMS
Key-value store

Time Series DBMS

Relational DBMS

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

Score	1.90
Rank	#126	Overall
	#23	Document stores
	#60	Relational DBMS

Score	0.56
Rank	#241	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	0.05
Rank	#357	Overall
	#151	Relational DBMS

Website

drill.apache.org

www.graphengine.io

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

www.oushu.com/product/oushuDB

Technical documentation

drill.apache.org/docs

www.graphengine.io/docs/manual

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

www.oushu.com/documentation

Developer

Apache Software Foundation

Microsoft

Circonus LLC.

Oushu

Initial release

2012

2010

2017

Current release

1.20.3, January 2023

V0.10.20, January 2018

4.0.1, August 2020

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

MIT License

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

.NET and C

C and C++

Server operating systems

Linux
OS X
Windows

.NET

Linux

Data scheme

schema-free

yes

schema-free

yes

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

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

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

Full-featured ANSI SQL support

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

RESTful HTTP API

HTTP API

JDBC
ODBC

Supported programming languages

C++

C#
C++
F#
Visual Basic

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

C
C++

Server-side scripts

Stored procedures

user defined functions

yes

yes, in Lua

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Automatic, metric affinity per node

yes

Replication methods

Methods for redundantly storing data on multiple nodes

configurable replication factor, datacenter aware

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate consistency per node, eventual consistency across nodes

Foreign keys

Referential integrity

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

Depending on the underlying data source

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

yes

User concepts

Access control

Depending on the underlying data source

Kerberos, SSL and role based access

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More resources

Recent citations in the news

Apache Drill case study: A tutorial on processing CSV files
9 June 2016, TheServerSide.com

Analyse Kafka messages with SQL queries using Apache Drill
27 September 2019, Towards Data Science

MapR Advances Support for Flexible and High Performance Analytics on JSON and S3 Data with Apache Drill
30 January 2019, businesswire.com

Apache Drill Adds New Data Formats
28 March 2022, iProgrammer

Apache Drill Eliminates ETL, Data Transformation for MapR Database
11 April 2016, The New Stack

provided by Google News

Trinity
30 October 2010, Microsoft

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13 February 2017, InfoWorld

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27 July 2016, GeekWire

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21 February 2024, SiliconANGLE News

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21 February 2024, Enterprise Times

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8 September 2021, PingWest

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