DBMS > Apache Drill vs. Datomic vs. DuckDB vs. HyperSQL

System Properties Comparison Apache Drill vs. Datomic vs. DuckDB vs. HyperSQL

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Editorial information provided by DB-Engines

Name

Description

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

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

An embeddable, in-process, column-oriented SQL OLAP RDBMS

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Primary database model

Document store
Relational DBMS

Relational 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	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	4.57
Rank	#74	Overall
	#40	Relational DBMS

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

Website

Technical documentation

drill.apache.org/docs

docs.datomic.com

duckdb.org/docs

hsqldb.org/web/hsqlDocsFrame.html

Developer

Apache Software Foundation

Cognitect

Initial release

2012

2018

2001

Current release

1.20.3, January 2023

1.0.6735, June 2023

0.10, February 2024

2.7.2, June 2023

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

limited edition free

Open Source

MIT License

Open Source

based on BSD license

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, Clojure

C++

Java

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

server-less

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Data scheme

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.

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

RESTful HTTP API

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

HTTP API

JDBC via HTTP
JDBC
ODBC

Supported programming languages

C++

Clojure
Java

C
C#

3rd party driver
C++
Crystal

3rd party driver
Go

3rd party driver
Java
Lisp

3rd party driver
Python
R
Ruby

3rd party driver
Rust
Swift
Zig

3rd party driver

All languages supporting JDBC/ODBC
Java

Server-side scripts

Stored procedures

user defined functions

yes

Transaction Functions

Java, SQL

Triggers

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

But extensive use of caching in the application peers

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

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

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

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

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

recommended only for testing and development

yes

User concepts

Access control

Depending on the underlying data source

fine grained access rights according to SQL-standard

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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
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

Drill Mines Diverse Data Sets, Google Style
20 May 2015, The Next Platform

provided by Google News

Nubank buys firm behind Clojure programming language
28 July 2020, Finextra

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1 December 2020, The New Stack

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24 July 2020, LatamList

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15 May 2024, InfoWorld

DuckDB Walks to the Beat of Its Own Analytics Drum
5 March 2024, Datanami

Enabling Remote Query Execution through DuckDB Extensions
12 March 2024, InfoQ.com

My First Billion (of Rows) in DuckDB | by João Pedro | May, 2024
1 May 2024, Towards Data Science

MotherDuck Raises $52.5 Million Series B Funding as DuckDB Adoption Soars
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24 October 2022, The Daily Swig

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