DBMS > Elasticsearch vs. Google Cloud Firestore vs. Graphite vs. SQL.JS vs. VoltDB

System Properties Comparison Elasticsearch vs. Google Cloud Firestore vs. Graphite vs. SQL.JS vs. VoltDB

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.

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Port of SQLite to JavaScript

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

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	132.83
Rank	#7	Overall
	#1	Search engines

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	4.83
Rank	#67	Overall
	#4	Time Series DBMS

Score	0.63
Rank	#241	Overall
	#112	Relational DBMS

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

www.elastic.co/elasticsearch

firebase.google.com/products/firestore

github.com/graphite-project/graphite-web

sql.js.org

www.voltdb.com

Technical documentation

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

firebase.google.com/docs/firestore

graphite.readthedocs.io

sql.js.org/documentation/index.html

docs.voltdb.com

Developer

Elastic

Google

Chris Davis

Alon Zakai

enhancements implemented by others

VoltDB Inc.

Initial release

2010

2017

2006

2012

2010

Current release

8.6, January 2023

11.3, April 2022

License

Commercial or Open Source

Open Source

Elastic License

commercial

Open Source

Apache 2.0

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

Python

JavaScript

Java, C++

Server operating systems

All OS with a Java VM

hosted

Linux
Unix

server-less, requires a JavaScript environment (browser, Node.js)

Linux
OS X

for development

Data scheme

schema-free

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

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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-92 is not fully supported

yes

only a subset of SQL 99

APIs and other access methods

Java API
RESTful HTTP/JSON API

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

HTTP API
Sockets

JavaScript API

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

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

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

JavaScript (Node.js)
Python

JavaScript

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

yes, Firebase Rules & Cloud Functions

Java

Triggers

yes

by using the 'percolation' feature

yes, with Cloud Functions

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

none

Multi-source replication
Source-replica replication

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

none

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

yes

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

locking

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

except by serializing a db to a file

yes

Snapshots and command logging

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.

Users and roles with access to stored procedures

More information provided by the system vendor

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Related products and services

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More resources

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