DBMS > Amazon CloudSearch vs. Elasticsearch vs. IBM Db2 Event Store vs. SQLite

System Properties Comparison Amazon CloudSearch vs. Elasticsearch vs. IBM Db2 Event Store vs. SQLite

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Editorial information provided by DB-Engines

Name

Description

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

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

Distributed Event Store optimized for Internet of Things use cases

Widely used embeddable, in-process RDBMS

Primary database model

Search engine

Event Store
Time Series DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS
Vector DBMS

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

Score	1.87
Rank	#140	Overall
	#12	Search engines

Score	134.78
Rank	#7	Overall
	#1	Search engines

Score	0.23
Rank	#316	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	116.01
Rank	#10	Overall
	#7	Relational DBMS

Website

aws.amazon.com/cloudsearch

www.elastic.co/elasticsearch

www.ibm.com/products/db2-event-store

www.sqlite.org

Technical documentation

docs.aws.amazon.com/cloudsearch

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

www.ibm.com/docs/en/db2-event-store

www.sqlite.org/docs.html

Developer

Amazon

Elastic

IBM

Dwayne Richard Hipp

Initial release

2012

2010

2017

2000

Current release

8.6, January 2023

2.0

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

commercial

Open Source

Elastic License

commercial

free developer edition available

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.

Implementation language

Java

C and C++

Server operating systems

hosted

All OS with a Java VM

Linux

Linux, macOS, Windows for the developer addition

server-less

Data scheme

yes

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.

Secondary indexes

yes

all search fields are automatically indexed

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

through the embedded Spark runtime

yes

SQL-92 is not fully supported

APIs and other access methods

HTTP API

Java API
RESTful HTTP/JSON API

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

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

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

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

yes

automatic partitioning across Amazon Search Instance as required

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

yes

Active-active shard replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

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

Eventual 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

No - written data is immutable

yes

via file-system locks

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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

authentication via encrypted signatures

fine grained access rights according to SQL-standard

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