DBMS > Apache Druid vs. DuckDB vs. GeoMesa vs. Sadas Engine

System Properties Comparison Apache Druid vs. DuckDB vs. GeoMesa vs. Sadas Engine

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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

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

Spatial DBMS

Relational DBMS

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

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	4.57
Rank	#74	Overall
	#40	Relational DBMS

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Website

Technical documentation

druid.apache.org/docs/latest/design

duckdb.org/docs

www.geomesa.org/documentation/stable/user/index.html

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Apache Software Foundation and contributors

CCRi and others

SADAS s.r.l.

Initial release

2012

2018

2014

2006

Current release

29.0.1, April 2024

0.10, February 2024

4.0.5, February 2024

8.0

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

MIT License

Open Source

Apache License 2.0

commercial

free trial version available

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++

Scala

C++

Server operating systems

Linux
OS X
Unix

server-less

AIX
Linux
Windows

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

APIs and other access methods

JDBC
RESTful HTTP/JSON API

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

JDBC
ODBC
Proprietary protocol

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

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

depending on storage layer

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

none

depending on storage layer

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

depending on storage layer

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

In-memory capabilities

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

yes

depending on storage layer

yes

managed by 'Learn by Usage'

User concepts

Access control

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

yes

depending on the DBMS used for storage

Access rights for users, groups and roles according to SQL-standard

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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