DBMS > Google Cloud Firestore vs. Graph Engine vs. Manticore Search vs. XTDB

System Properties Comparison Google Cloud Firestore vs. Graph Engine vs. Manticore Search vs. XTDB

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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.

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

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

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Document store

Graph DBMS
Key-value store

Search engine

Document store

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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

Score	6.63
Rank	#54	Overall
	#9	Document stores

Score	0.56
Rank	#241	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	0.23
Rank	#301	Overall
	#21	Search engines

Score	0.13
Rank	#330	Overall
	#45	Document stores

Website

firebase.google.com/products/firestore

www.graphengine.io

manticoresearch.com

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

firebase.google.com/docs/firestore

www.graphengine.io/docs/manual

manual.manticoresearch.com

www.xtdb.com/docs

Developer

Google

Microsoft

Manticore Software

Juxt Ltd.

Initial release

2017

2010

2017

2019

Current release

6.0, February 2023

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

MIT License

Open Source

GPL version 2

Open Source

MIT License

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

.NET and C

C++

Clojure

Server operating systems

hosted

.NET

FreeBSD
Linux
macOS
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free

yes

Fixed schema

schema-free

Typing

predefined data types such as float or date

yes

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

yes, extensible-data-notation format

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

yes

SQL

Support of SQL

SQL-like query language

limited SQL, making use of Apache Calcite

APIs and other access methods

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

RESTful HTTP API

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

HTTP REST
JDBC

Supported programming languages

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

C#
C++
F#
Visual Basic

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

Clojure
Java

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

yes

user defined functions

Triggers

yes, with Cloud Functions

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Synchronous replication based on Galera library

yes, each node contains all data

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

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

The original contents of fields are not stored in the Manticore index.

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

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

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

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