DBMS > Amazon DynamoDB vs. Elasticsearch vs. Firebird vs. Manticore Search

System Properties Comparison Amazon DynamoDB vs. Elasticsearch vs. Firebird vs. Manticore Search

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Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database 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

Firebird is an open source RDBMS forked from Borland's InterBase

Multi-storage database for search, including full-text search.

Primary database model

Document store
Key-value store

Search engine

Relational DBMS

Search engine

Secondary database models

Document store
Spatial DBMS
Vector DBMS

Time Series DBMS

using the Manticore Columnar Library

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

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	135.35
Rank	#7	Overall
	#1	Search engines

Score	20.82
Rank	#30	Overall
	#18	Relational DBMS

Score	0.22
Rank	#312	Overall
	#21	Search engines

Website

aws.amazon.com/dynamodb

www.elastic.co/elasticsearch

www.firebirdsql.org

manticoresearch.com

Technical documentation

docs.aws.amazon.com/dynamodb

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

www.firebirdsql.org/en/reference-manuals

manual.manticoresearch.com

Developer

Amazon

Elastic

Firebird Foundation

Manticore Software

Initial release

2012

2010

2000

As fork of Borland's InterBase

2017

Current release

8.6, January 2023

5.0.0, January 2024

6.0, February 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Elastic License

Open Source

Initial Developer's Public License

Open Source

GPL version 2

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C and C++

C++

Server operating systems

hosted

All OS with a Java VM

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

FreeBSD
Linux
macOS
Windows

Data scheme

schema-free

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

yes

Fixed schema

Typing

predefined data types such as float or date

yes

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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.

Can index from XML

Secondary indexes

yes

All search fields are automatically indexed

yes

full-text index on all search fields

SQL

Support of SQL

SQL-like query language

yes

SQL-like query language

APIs and other access methods

RESTful HTTP API

Java API
RESTful HTTP/JSON API

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

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

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

Server-side scripts

Stored procedures

yes

PSQL

user defined functions

Triggers

yes

by integration with AWS Lambda

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

Synchronous replication based on Galera library

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

ACID

yes

isolated transactions for atomic changes and binary logging for safe writes

Concurrency

Support for concurrent manipulation of data

yes

Features a multi-generational MVCC architecture, readers do not block writers

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Manticore index.

In-memory capabilities

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

Memcached and Redis integration

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Users with fine-grained authorization concept

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