DBMS > Amazon Redshift vs. Elasticsearch vs. FileMaker vs. IRONdb

System Properties Comparison Amazon Redshift vs. Elasticsearch vs. FileMaker vs. IRONdb

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Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Large scale data warehouse service for use with business intelligence tools

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

FileMaker is a cross-platform RDBMS that includes a GUI frontend.

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

Primary database model

Secondary database models

Document store
Spatial DBMS
Vector DBMS

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

Score	19.03
Rank	#34	Overall
	#21	Relational DBMS

Score	134.78
Rank	#7	Overall
	#1	Search engines

Score	49.73
Rank	#20	Overall
	#14	Relational DBMS

Website

aws.amazon.com/redshift

www.elastic.co/elasticsearch

www.claris.com/filemaker

www.circonus.com/solutions/time-series-database/

Technical documentation

docs.aws.amazon.com/redshift

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

www.claris.com/resources/documentation

docs.circonus.com/irondb/category/getting-started

Developer

Amazon (based on PostgreSQL)

Elastic

Claris

a subsidiary of Apple

Circonus LLC.

Initial release

2012

2010

1983

2017

Current release

8.6, January 2023

19.4.1, November 2021

V0.10.20, January 2018

License

Commercial or Open Source

commercial

Open Source

Elastic License

commercial

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

iOS

client part only
Linux
OS X
Windows

Linux

Data scheme

yes

schema-free

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

yes

schema-free

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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

A http query request can return the data in XML format

Secondary indexes

restricted

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language

yes

via plugins

SQL-like query language (Circonus Analytics Query Language: CAQL)

APIs and other access methods

JDBC
ODBC

Java API
RESTful HTTP/JSON API

Filemaker WebDirect
JDBC
ODBC

HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

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

PHP

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

Server-side scripts

Stored procedures

user defined functions

in Python

yes

yes, in Lua

Triggers

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Automatic, metric affinity per node

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication, warm standby

since Version 14

configurable replication factor, datacenter aware

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

Immediate consistency per node, eventual consistency across nodes

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

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.

yes

Memcached and Redis integration

User concepts

Access control

fine grained access rights according to SQL-standard

simple rights management via user accounts and connection to external directory services

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