DBMS > DuckDB vs. Elasticsearch vs. FatDB

System Properties Comparison DuckDB vs. Elasticsearch vs. FatDB

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Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

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

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Primary database model

Relational DBMS

Search engine
Vector DBMS

Document store
Key-value store

Secondary database models

Document store
Spatial DBMS

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

Score	6.17
Rank	#55	Overall
	#33	Relational DBMS

Score	132.32
Rank	#8	Overall
	#1	Search engines
	#1	Vector DBMS

Website

duckdb.org

www.elastic.co/elasticsearch

Technical documentation

duckdb.org/docs

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

Developer

Elastic

FatCloud

Initial release

2018

2010

2012

Current release

1.0.0, June 2024

8.6, January 2023

License

Commercial or Open Source

Open Source

MIT License

Open Source

Elastic License

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.

Implementation language

C++

Java

Server operating systems

server-less

All OS with a Java VM

Windows

Data scheme

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

schema-free

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

All search fields are automatically indexed

yes

SQL

Support of SQL

yes

SQL-like query language

Via inetgration in SQL Server

APIs and other access methods

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

Java API
RESTful HTTP/JSON API

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

Supported programming languages

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
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

via applications

Triggers

yes

by using the 'percolation' feature

yes

via applications

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

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

Memcached and Redis integration

User concepts

Access control

Can implement custom security layer via applications

More information provided by the system vendor

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2017
2 January 2018, Paul Andlinger, Matthias Gelbmann

Elasticsearch moved into the top 10 most popular database management systems
3 July 2017, Matthias Gelbmann

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

show all

Recent citations in the news

A Guide to Data Analysis in Python with DuckDB
18 November 2024, KDnuggets

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

MotherDuck Announces Beta Release of pg_duckdb; Brings DuckDB's Analytics Power to PostgreSQL Users
24 October 2024, PR Newswire

Supercharge Your SQL Analysis with Python and DuckDB | by Jesus L. Monroy | T3CH | Nov, 2024
28 November 2024, Medium

DuckDB inside Postgres!!??
27 October 2024, substack.com

provided by Google News

Elastic's AI-powered data search: Unlocking business insights
4 December 2024, SiliconANGLE News

Elastic Introduces Better Binary Quantization Technique in Elasticsearch
11 November 2024, Business Wire

Elasticsearch Was Great, But Vector Databases Are the Future
18 November 2024, The New Stack

OpenSearch: Self-hosted, AWS Managed Or Serverless? | by Nikola Kucerova | Dec, 2024
8 December 2024, Medium

Amazon OpenSearch Service announces Standard and Extended Support dates for Elasticsearch and OpenSearch versions
7 November 2024, AWS Blog

provided by Google News

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