DBMS > Apache Drill vs. DataFS vs. Transwarp KunDB vs. Yaacomo

System Properties Comparison Apache Drill vs. DataFS vs. Transwarp KunDB vs. Yaacomo

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Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

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

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

OLTP DBMS based on a distributed architecture and highly compatible with MySQL and Oracle

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Document store
Relational DBMS

Object oriented DBMS

Relational DBMS

Secondary database models

Graph DBMS

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

Score	2.02
Rank	#124	Overall
	#22	Document stores
	#59	Relational DBMS

Score	0.09
Rank	#360	Overall
	#17	Object oriented DBMS

Score	0.14
Rank	#341	Overall
	#149	Relational DBMS

Website

drill.apache.org

newdatabase.com

www.transwarp.cn/en/product/kundb

yaacomo.com

Technical documentation

drill.apache.org/docs

dev.mobiland.com/Overview.xsp

Developer

Apache Software Foundation

Mobiland AG

Transwarp

Q2WEB GmbH

Initial release

2012

2018

2009

Current release

1.20.3, January 2023

1.1.263, October 2022

License

Commercial or Open Source

Open Source

Apache Version 2

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.

Server operating systems

Linux
OS X
Windows

Windows

Android
Linux
Windows

Data scheme

schema-free

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

yes

Typing

predefined data types such as float or date

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

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

.NET Client API
Proprietary client DLL
WinRT client

JDBC
ODBC

Supported programming languages

C++

.Net
C
C#
C++
VB.Net

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

no, except callback-events from server when changes happened

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Proprietary Sharding system

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

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

yes

User concepts

Access control

Depending on the underlying data source

Windows-Profile

yes

fine grained access rights according to SQL-standard

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More resources

Recent citations in the news

MapR to Speak on Stream Processing Systems, Apache Spark and Drill at Industry Events in January
31 May 2024, Yahoo Movies UK

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

Apache Drill vs. Apache Spark — Which SQL query engine is better for you?
23 September 2019, Towards Data Science

Apache Drill Poised to Crack Tough Data Challenges
19 May 2015, Datanami

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

provided by Google News

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