DBMS > Apache Druid vs. Citus vs. Coveo vs. Elasticsearch vs. RocksDB

System Properties Comparison Apache Druid vs. Citus vs. Coveo vs. Elasticsearch vs. RocksDB

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

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

AI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code development

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

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

Search engine

Key-value store

Secondary database models

Document store

Document store
Spatial DBMS
Vector 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	2.15
Rank	#117	Overall
	#56	Relational DBMS

Score	2.11
Rank	#118	Overall
	#11	Search engines

Score	132.83
Rank	#7	Overall
	#1	Search engines

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

druid.apache.org

www.citusdata.com

www.coveo.com

www.elastic.co/elasticsearch

rocksdb.org

Technical documentation

druid.apache.org/docs/latest/design

docs.citusdata.com

docs.coveo.com

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

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation and contributors

Coveo

Elastic

Facebook, Inc.

Initial release

2012

2010

2012

2010

2013

Current release

29.0.1, April 2024

8.1, December 2018

8.6, January 2023

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

AGPL, commercial license also available

commercial

Open Source

Elastic License

Open Source

BSD

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

Linux
OS X
Unix

Linux

hosted

All OS with a Java VM

Linux

Data scheme

yes

schema-less columns are supported

yes

hybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configuration

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.

yes

specific XML type available, but no XML query functionality

Secondary indexes

yes

All search fields are automatically indexed

SQL

Support of SQL

SQL for querying

yes

standard, with numerous extensions

SQL-like query language

APIs and other access methods

JDBC
RESTful HTTP/JSON API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

RESTful HTTP API

Java API
RESTful HTTP/JSON API

C++ API
Java API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C#
Java
JavaScript
Python

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

yes

Triggers

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

yes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Source-replica replication

other methods possible by using 3rd party extensions

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

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.

Memcached and Redis integration

yes

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

granular access controls, API key management, content filters

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