DBMS > Badger vs. Google Cloud Firestore vs. Manticore Search

System Properties Comparison Badger vs. Google Cloud Firestore vs. Manticore Search

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Editorial information provided by DB-Engines

Name

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

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.

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

Primary database model

Key-value store

Document store

Search engine

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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

Score	0.14
Rank	#331	Overall
	#49	Key-value stores

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	0.22
Rank	#312	Overall
	#21	Search engines

Website

github.com/dgraph-io/badger

firebase.google.com/products/firestore

manticoresearch.com

Technical documentation

godoc.org/github.com/dgraph-io/badger

firebase.google.com/docs/firestore

manual.manticoresearch.com

Developer

DGraph Labs

Google

Manticore Software

Initial release

2017

Current release

6.0, February 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

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

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

hosted

FreeBSD
Linux
macOS
Windows

Data scheme

schema-free

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

full-text index on all search fields

SQL

Support of SQL

SQL-like query language

APIs and other access methods

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

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

Supported programming languages

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

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

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

user defined functions

Triggers

yes, with Cloud Functions

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

Synchronous replication based on Galera library

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

isolated transactions for atomic changes and binary logging for safe writes

Concurrency

Support for concurrent manipulation of data

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.

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

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