DBMS > Google Cloud Firestore vs. RocksDB vs. VelocityDB vs. Warp 10

System Properties Comparison Google Cloud Firestore vs. RocksDB vs. VelocityDB vs. Warp 10

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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.

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

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

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Document store

Key-value store

Graph DBMS
Object oriented DBMS

Time Series DBMS

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

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

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

Score	0.07
Rank	#349	Overall
	#32	Time Series DBMS

Website

firebase.google.com/products/firestore

rocksdb.org

velocitydb.com

www.warp10.io

Technical documentation

firebase.google.com/docs/firestore

github.com/facebook/rocksdb/wiki

velocitydb.com/UserGuide

www.warp10.io/content/02_Getting_started

Developer

Google

Facebook, Inc.

VelocityDB Inc

SenX

Initial release

2017

2013

2011

2015

Current release

8.11.4, April 2024

7.x

License

Commercial or Open Source

commercial

Open Source

BSD

commercial

Open Source

Apache License 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++

Java

Server operating systems

hosted

Linux

Any that supports .NET

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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

SQL

Support of SQL

APIs and other access methods

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

C++ API
Java API

.Net

HTTP API
Jupyter
WebSocket

Supported programming languages

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

C
C++
Go
Java
Perl
Python
Ruby

.Net

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

yes

WarpScript

Triggers

yes, with Cloud Functions

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

selectable replication factor

based on HBase

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

based on HBase

Foreign keys

Referential integrity

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

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.

Based on Windows Authentication

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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