DBMS > Elasticsearch vs. EventStoreDB vs. Google Cloud Firestore vs. SwayDB

System Properties Comparison Elasticsearch vs. EventStoreDB vs. Google Cloud Firestore vs. SwayDB

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Editorial information provided by DB-Engines

Name

Description

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

Industrial-strength, open-source database solution built from the ground up for event sourcing.

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

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	135.35
Rank	#7	Overall
	#1	Search engines

Score	1.10
Rank	#179	Overall
	#1	Event Stores

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Website

www.elastic.co/elasticsearch

www.eventstore.com

firebase.google.com/products/firestore

swaydb.simer.au

Technical documentation

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

developers.eventstore.com

firebase.google.com/docs/firestore

Developer

Elastic

Event Store Limited

Google

Simer Plaha

Initial release

2010

2012

2017

2018

Current release

8.6, January 2023

21.2, February 2021

License

Commercial or Open Source

Open Source

Elastic License

Open Source

commercial

Open Source

GNU Affero GPL V3.0

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

Scala

Server operating systems

All OS with a Java VM

Linux
Windows

hosted

Data scheme

schema-free

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

schema-free

Typing

predefined data types such as float or date

yes

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-like query language

APIs and other access methods

Java API
RESTful HTTP/JSON API

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

Supported programming languages

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

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

Java
Kotlin
Scala

Server-side scripts

Stored procedures

yes

yes, Firebase Rules & Cloud Functions

Triggers

yes

by using the 'percolation' feature

yes, with Cloud Functions

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

Using Cloud Dataflow

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

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

Atomic execution of operations

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.

Memcached and Redis integration

yes

User concepts

Access control

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

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More resources

DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2017
2 January 2018, Paul Andlinger, Matthias Gelbmann

Elasticsearch moved into the top 10 most popular database management systems
3 July 2017, Matthias Gelbmann

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

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Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

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Recent citations in the news

Netflix Uses Elasticsearch Percolate Queries to Implement Reverse Searches Efficiently
29 April 2024, InfoQ.com

Elasticsearch Changes Name to Elastic to Reflect Wide Adoption Beyond Search
29 April 2024, Yahoo Singapore News

Elastic Reports 8x Speed and 32x Efficiency Gains for Elasticsearch and Lucene Vector Database
26 April 2024, Business Wire

The end of vendor-backed open source?
29 April 2024, InfoWorld

Splunk vs Elasticsearch | A Comparison and How to Choose
12 January 2024, SentinelOne

provided by Google News

Realtime vs Cloud Firestore: Which Firebase Database to go?
8 March 2024, Appinventiv

Google's AI-First Strategy Brings Vector Support To Cloud Databases
1 March 2024, Forbes

Google’s Firebase gets AI extensions, opens up its marketplace
10 May 2023, TechCrunch

Google's Cloud Firestore is now generally available
31 January 2019, ZDNet

Firestore and Python | NoSQL on Google Cloud
7 August 2020, Towards Data Science

provided by Google News

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