DBMS > Amazon CloudSearch vs. Apache Druid vs. Apache Phoenix vs. SQLite vs. YottaDB

System Properties Comparison Amazon CloudSearch vs. Apache Druid vs. Apache Phoenix vs. SQLite vs. YottaDB

Editorial information provided by DB-Engines

Name

Description

A hosted search engine service by Amazon with the data stored in Amazons cloud

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

A scale-out RDBMS with evolutionary schema built on Apache HBase

Widely used embeddable, in-process RDBMS

A fast and solid embedded Key-value store

Primary database model

Search engine

Relational DBMS
Time Series DBMS

Relational DBMS

Key-value store

Secondary database models

Relational DBMS

using the Octo plugin

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

Score	1.81
Rank	#137	Overall
	#12	Search engines

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	2.06
Rank	#123	Overall
	#58	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	0.28
Rank	#306	Overall
	#44	Key-value stores

Website

aws.amazon.com/cloudsearch

Technical documentation

docs.aws.amazon.com/cloudsearch

druid.apache.org/docs/latest/design

phoenix.apache.org

www.sqlite.org/docs.html

yottadb.com/resources/documentation

Developer

Amazon

Apache Software Foundation and contributors

Apache Software Foundation

Dwayne Richard Hipp

YottaDB, LLC

Initial release

2012

2014

2000

2001

Current release

29.0.1, April 2024

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

Open Source

Apache license v2

Open Source

Apache Version 2.0

Open Source

Public Domain

Open Source

AGPL 3.0

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.

Implementation language

Java

Server operating systems

hosted

Linux
OS X
Unix

Linux
Unix
Windows

server-less

Docker
Linux

Data scheme

yes

schema-less columns are supported

yes

late-bound, schema-on-read capabilities

yes

dynamic column types

schema-free

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.

Secondary indexes

yes

all search fields are automatically indexed

yes

SQL

Support of SQL

SQL for querying

yes

SQL-92 is not fully supported

by using the Octo plugin

APIs and other access methods

HTTP API

JDBC
RESTful HTTP/JSON API

JDBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

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

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

Sharding

manual/auto, time-based

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

yes, via HDFS, S3 or other storage engines

Multi-source replication
Source-replica replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

User concepts

Access control

authentication via encrypted signatures

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

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

Users and groups based on OS-security mechanisms

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