DBMS > Google Cloud Firestore vs. OrigoDB vs. Sphinx vs. VelocityDB

System Properties Comparison Google Cloud Firestore vs. OrigoDB vs. Sphinx vs. VelocityDB

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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 fully ACID in-memory object graph database

Open source search engine for searching in data from different sources, e.g. relational databases

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Document store

Document store
Object oriented DBMS

Search engine

Graph DBMS
Object oriented DBMS

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

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Score	0.05
Rank	#358	Overall
	#36	Graph DBMS
	#16	Object oriented DBMS

Website

firebase.google.com/products/firestore

origodb.com

sphinxsearch.com

velocitydb.com

Technical documentation

firebase.google.com/docs/firestore

origodb.com/docs

sphinxsearch.com/docs

velocitydb.com/UserGuide

Developer

Google

Robert Friberg et al

Sphinx Technologies Inc.

VelocityDB Inc

Initial release

2017

2009

under the name LiveDB

2001

2011

Current release

3.5.1, February 2023

7.x

License

Commercial or Open Source

commercial

Open Source

GPL version 2, commercial licence available

commercial

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

Linux
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Any that supports .NET

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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 be achieved using .NET

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

SQL-like query language (SphinxQL)

APIs and other access methods

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

.NET Client API
HTTP API
LINQ

Proprietary protocol

.Net

Supported programming languages

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

.Net

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

.Net

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

yes

Triggers

yes, with Cloud Functions

yes

Domain Events

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

client side managed; servers are not synchronized

Sharding

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication

none

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

depending on model

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

yes

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

yes

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.

Role based authorization

Based on Windows Authentication

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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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The DB-Engines ranking includes now search engines
4 February 2013, Paul Andlinger

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