DBMS > Badger vs. DuckDB vs. Elasticsearch vs. TerarkDB

System Properties Comparison Badger vs. DuckDB vs. Elasticsearch vs. TerarkDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

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 key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Secondary database models

Document store
Spatial DBMS
Vector DBMS

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

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	4.63
Rank	#69	Overall
	#37	Relational DBMS

Score	132.83
Rank	#7	Overall
	#1	Search engines

Score	0.08
Rank	#367	Overall
	#56	Key-value stores

Website

github.com/dgraph-io/badger

duckdb.org

www.elastic.co/elasticsearch

github.com/bytedance/terarkdb

Technical documentation

godoc.org/github.com/dgraph-io/badger

duckdb.org/docs

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

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

DGraph Labs

Elastic

ByteDance, originally Terark

Initial release

2017

2018

2010

2016

Current release

1.0.0, June 2024

8.6, January 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

MIT License

Open Source

Elastic License

commercial

restricted open source 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

C++

Java

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

server-less

All OS with a Java VM

Data scheme

schema-free

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

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

Java API
RESTful HTTP/JSON API

C++ API
Java API

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

C++
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

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

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

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

yes

User concepts

Access control

More information provided by the system vendor

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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

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5 June 2024, The Register

DuckDB: The tiny but powerful analytics database
15 May 2024, InfoWorld

DuckDB 1.0 Released
4 June 2024, iProgrammer

DuckDB: In-Process Python Analytics for Not-Quite-Big Data
31 May 2024, The New Stack

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

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25 April 2024, Yahoo Finance

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12 January 2024, SentinelOne

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26 March 2024, insider.govtech.com

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29 April 2024, InfoQ.com

provided by Google News

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