DBMS > Apache Drill vs. Apache Kylin vs. DolphinDB vs. Oracle Berkeley DB vs. Trafodion

System Properties Comparison Apache Drill vs. Apache Kylin vs. DolphinDB vs. Oracle Berkeley DB vs. Trafodion

Editorial information provided by DB-Engines

Name

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

Description

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

A distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stack

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

Widely used in-process key-value store

Transactional SQL-on-Hadoop DBMS

Primary database model

Document store
Relational DBMS

Relational DBMS

Time Series DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Relational DBMS

Secondary database models

Relational 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	1.25
Rank	#170	Overall
	#77	Relational DBMS

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	2.01
Rank	#126	Overall
	#21	Key-value stores
	#3	Native XML DBMS

Website

drill.apache.org

kylin.apache.org

www.dolphindb.com

www.oracle.com/database/technologies/related/berkeleydb.html

trafodion.apache.org

Technical documentation

drill.apache.org/docs

kylin.apache.org/docs

docs.dolphindb.cn/en/help200/index.html

docs.oracle.com/cd/E17076_05/html/index.html

trafodion.apache.org/documentation.html

Developer

Apache Software Foundation

Apache Software Foundation, originally contributed from eBay Inc

DolphinDB, Inc

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Apache Software Foundation, originally developed by HP

Initial release

2012

2015

2018

1994

2014

Current release

1.20.3, January 2023

3.1.0, July 2020

v2.00.4, January 2022

18.1.40, May 2020

2.3.0, February 2019

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2.0

commercial

free community version available

Open Source

commercial license available

Open Source

Apache 2.0

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

Java

C++

C, Java, C++ (depending on the Berkeley DB edition)

C++, Java

Server operating systems

Linux
OS X
Windows

Linux

Linux
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux

Data scheme

schema-free

yes

schema-free

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.

yes

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

ANSI SQL for queries (using Apache Calcite)

SQL-like query language

yes

SQL interfaced based on SQLite is available

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

ADO.NET
JDBC
ODBC

Supported programming languages

C++

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

user defined functions

yes

Java Stored Procedures

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes, via HBase

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

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

yes

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

Administrators, Users, Groups

fine grained access rights according to SQL-standard

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