DBMS > Elasticsearch vs. Google Cloud Firestore vs. Sadas Engine vs. SWC-DB

System Properties Comparison Elasticsearch vs. Google Cloud Firestore vs. Sadas Engine vs. SWC-DB

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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

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.

SADAS Engine is a columnar DBMS specifically designed for high performance in Data warehouse environments

A high performance, scalable Wide Column DBMS

Primary database model

Secondary database models

Document store
Spatial DBMS

Time Series DBMS

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

Score	157.69
Rank	#8	Overall
	#1	Search engines

Score	9.32
Rank	#52	Overall
	#10	Document stores

Score	0.00
Rank	#354	Overall
	#152	Relational DBMS

Score	0.01
Rank	#350	Overall
	#13	Wide column stores

Website

www.elastic.co/elasticsearch

firebase.google.com/products/firestore

www.sadasengine.com

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

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

firebase.google.com/docs/firestore

www.sadasengine.com/index.php/downloads/documentation-columnar-db

Developer

Elastic

Google

SADAS s.r.l.

Alex Kashirin

Initial release

2010

2017

2006

2020

Current release

7.8.0, June 2020

8.0

0.5, April 2021

License

Commercial or Open Source

Open Source

Elastic License

commercial

free trial version available

Open Source

GPL V3

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++

Server operating systems

All OS with a Java VM

hosted

AIX
Linux
Windows

Linux

Data scheme

schema-free

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

schema-free

yes

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

yes

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

JDBC
ODBC
Proprietary protocol

Proprietary protocol
Thrift

Supported programming languages

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

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

.Net
C
C#
C++
Groovy
Java
PHP
Python

C++

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

horizontal partitioning

Sharding

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

yes

Transaction concepts

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

yes

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

managed by 'Learn by Usage'

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.

Access rights for users, groups and roles according to SQL-standard

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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

show all

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

show all

Recent citations in the news

Once frenemies, Elastic and AWS are now besties
19 May 2022, VentureBeat

Exposed ElasticSearch server compromises thousands of borrowers
6 May 2022, SC Media

Misconfigured ElasticSearch Servers Exposed 579 GB of Users' Website Activity
12 May 2022, HackRead

Former AWS engineer sets out to build a better log search engine
19 May 2022, TechCrunch

Elastic Announces New Capabilities to Help Customers Solve Their Biggest Business Challenges
3 May 2022, Business Wire

provided by Google News

Google Cloud Launches New Postgres-Compatible Database, AlloyDB
11 May 2022, Datanami

Google's Firebase app development platform gets updates and security boosts
11 May 2022, SiliconANGLE News

Google's Data Cloud Summit Serves Up Incremental New Capabilities
25 April 2022, Forbes

Kill some time waiting for Google I/O to start with its official pinball game
10 May 2022, Android Police

Google’s Cloud Firestore NoSQL database hits general availability
31 January 2019, TechCrunch

provided by Google News

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