DBMS > Apache Druid vs. Databricks vs. OpenSearch vs. SQL.JS vs. SQLite

System Properties Comparison Apache Druid vs. Databricks vs. OpenSearch vs. SQL.JS vs. SQLite

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

The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.

A distributed, RESTful search and analytics engine forked from Elasticsearch and based on Apache Lucene

Port of SQLite to JavaScript

Widely used embeddable, in-process RDBMS

Primary database model

Relational DBMS
Time Series DBMS

Document store
Relational DBMS

Search engine

Relational DBMS

Secondary database models

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	81.08
Rank	#15	Overall
	#2	Document stores
	#10	Relational DBMS

Score	16.03
Rank	#37	Overall
	#4	Search engines

Score	0.63
Rank	#241	Overall
	#112	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

druid.apache.org

www.databricks.com

github.com/opensearch-project
opensearch.org

sql.js.org

www.sqlite.org

Technical documentation

druid.apache.org/docs/latest/design

docs.databricks.com

opensearch.org/docs/latest

sql.js.org/documentation/index.html

www.sqlite.org/docs.html

Developer

Apache Software Foundation and contributors

Databricks

Amazon Web Services

Alon Zakai

enhancements implemented by others

Dwayne Richard Hipp

Initial release

2012

2013

2021

2012

2000

Current release

29.0.1, April 2024

2.5.0, January 2023

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

Apache license v2

commercial

Open Source

Apache Version 2.0

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

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Implementation language

Java

JavaScript

Server operating systems

Linux
OS X
Unix

hosted

All OS with a Java VM

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

server-less

Data scheme

yes

schema-less columns are supported

Flexible Schema (defined schema, partial schema, schema free)

schema-free

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

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

Secondary indexes

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL for querying

with Databricks SQL

SQL-like query language

yes

SQL-92 is not fully supported

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
RESTful HTTP/JSON API

JDBC
ODBC
RESTful HTTP API

Java API
RESTful HTTP/JSON API

JavaScript API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Python
R
Scala

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

JavaScript

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

Triggers

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

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

none

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

via file-system locks

Durability

Support for making data persistent

yes

except by serializing a db to a file

yes

In-memory capabilities

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

yes

User concepts

Access control

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

More information provided by the system vendor

Specific characteristics

Supported database models : In addition to the Document store and Relational DBMS...
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OpenSearch is a highly scalable and extensible open-source software suite for search,...
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Competitive advantages

Distributed as fully open source under Apache License, Version 2.0 (ALv2), OpenSearch...
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Typical application scenarios

The OpenSearch platform is used across a broad range of search , analytics, and observability...
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Licensing and pricing models

The OpenSearch Project offers open source software licensed under Apache License...
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