DBMS > Apache Druid vs. Elasticsearch vs. Hypertable vs. Quasardb vs. SQLite

System Properties Comparison Apache Druid vs. Elasticsearch vs. Hypertable vs. Quasardb vs. SQLite

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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

An open source BigTable implementation based on distributed file systems such as Hadoop

Distributed, high-performance timeseries database

Widely used embeddable, in-process RDBMS

Primary database model

Relational DBMS
Time Series DBMS

Secondary database models

Document store
Spatial DBMS
Vector 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	135.35
Rank	#7	Overall
	#1	Search engines

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

druid.apache.org

www.elastic.co/elasticsearch

quasar.ai

www.sqlite.org

Technical documentation

druid.apache.org/docs/latest/design

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

doc.quasar.ai/master

www.sqlite.org/docs.html

Developer

Apache Software Foundation and contributors

Elastic

Hypertable Inc.

quasardb

Dwayne Richard Hipp

Initial release

2012

2010

2009

2000

Current release

29.0.1, April 2024

8.6, January 2023

0.9.8.11, March 2016

3.14.1, January 2024

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Elastic License

Open Source

GNU version 3. Commercial license available

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

Public Domain

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++

Server operating systems

Linux
OS X
Unix

All OS with a Java VM

Linux
OS X
Windows

an inofficial Windows port is available

BSD
Linux
OS X
Windows

server-less

Data scheme

yes

schema-less columns are supported

schema-free

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

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

integer and binary

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.

Secondary indexes

yes

All search fields are automatically indexed

restricted

only exact value or prefix value scans

yes

with tags

yes

SQL

Support of SQL

SQL for querying

SQL-like query language

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
RESTful HTTP/JSON API

Java API
RESTful HTTP/JSON API

C++ API
Thrift

HTTP API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

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

C++
Java
Perl
PHP
Python
Ruby

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

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

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

consistent hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes

selectable replication factor on file system level

Source-replica replication with selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

yes

with Hadoop integration

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

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

via file-system locks

Durability

Support for making data persistent

yes

by using LevelDB

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

Transient mode

yes

User concepts

Access control

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

Cryptographically strong user authentication and audit trail

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