DBMS > Apache Druid vs. DuckDB vs. EsgynDB vs. Lovefield

System Properties Comparison Apache Druid vs. DuckDB vs. EsgynDB vs. Lovefield

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Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Embeddable relational database for web apps written in pure JavaScript

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

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

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	4.63
Rank	#69	Overall
	#37	Relational DBMS

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Website

druid.apache.org

duckdb.org

www.esgyn.cn

google.github.io/lovefield

Technical documentation

druid.apache.org/docs/latest/design

duckdb.org/docs

github.com/google/lovefield/blob/master/docs/spec_index.md

Developer

Apache Software Foundation and contributors

Esgyn

Google

Initial release

2012

2018

2015

2014

Current release

29.0.1, April 2024

1.0.0, June 2024

2.1.12, February 2017

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

MIT License

commercial

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

JavaScript

Server operating systems

Linux
OS X
Unix

server-less

Linux

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Data scheme

yes

schema-less columns are supported

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 for querying

yes

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

JDBC
RESTful HTTP/JSON API

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

ADO.NET
JDBC
ODBC

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

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/ADO.Net

JavaScript

Server-side scripts

Stored procedures

Java Stored Procedures

Triggers

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

none

Multi-source replication between multi datacenters

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

fine grained access rights according to SQL-standard

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More resources

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