DBMS > Google Cloud Firestore vs. Manticore Search vs. Memcached vs. Snowflake vs. VictoriaMetrics

System Properties Comparison Google Cloud Firestore vs. Manticore Search vs. Memcached vs. Snowflake vs. VictoriaMetrics

Editorial information provided by DB-Engines

Name

Description

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.

In-memory key-value store, originally intended for caching

Cloud-based data warehousing service for structured and semi-structured data

A fast, cost-effective and scalable Time Series DBMS and monitoring solution

Primary database model

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	0.29
Rank	#302	Overall
	#21	Search engines

Score	18.08
Rank	#32	Overall
	#4	Key-value stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	1.23
Rank	#172	Overall
	#15	Time Series DBMS

Website

firebase.google.com/products/firestore

Technical documentation

firebase.google.com/docs/firestore

manual.manticoresearch.com

github.com/memcached/memcached/wiki

docs.snowflake.net/manuals/index.html

docs.victoriametrics.com
github.com/VictoriaMetrics/VictoriaMetrics/wiki

Developer

Google

Manticore Software

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Snowflake Computing Inc.

VictoriaMetrics

Initial release

2017

2003

2014

2018

Current release

6.0, February 2023

1.6.27, May 2024

v1.91, May 2023

License

Commercial or Open Source

commercial

Open Source

GPL version 2

Open Source

BSD license

commercial

Open Source

Apache Version 2.0

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

C++

Server operating systems

hosted

FreeBSD
Linux
macOS
Windows

FreeBSD
Linux
OS X
Unix
Windows

hosted

FreeBSD
Linux
macOS
OpenBSD

Data scheme

schema-free

Fixed schema

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes

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

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.

Can index from XML

yes

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

SQL-like query language

yes

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

Proprietary protocol

CLI Client
JDBC
ODBC

Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write

Supported programming languages

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

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

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

user defined functions

Triggers

yes, with Cloud Functions

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Synchronous replication based on Galera library

none

Repcached, a Memcached patch, provides this functionallity

yes

Synchronous replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

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

ACID

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.

yes

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.

yes

using SASL (Simple Authentication and Security Layer) protocol

Users with fine-grained authorization concept, user roles and pluggable authentication

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