DBMS > Firebase Realtime Database vs. RavenDB vs. Snowflake vs. Splice Machine vs. SWC-DB

System Properties Comparison Firebase Realtime Database vs. RavenDB vs. Snowflake vs. Splice Machine vs. SWC-DB

Editorial information provided by DB-Engines

Name

Description

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

Open Source Operational and Transactional Enterprise NoSQL Document Database

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

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

A high performance, scalable Wide Column DBMS

Primary database model

Document store

Relational DBMS

Wide column store

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

Time Series DBMS

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

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	2.84
Rank	#101	Overall
	#18	Document stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Website

firebase.google.com/products/realtime-database

ravendb.net

www.snowflake.com

splicemachine.com

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

firebase.google.com/docs/database

ravendb.net/docs

docs.snowflake.net/manuals/index.html

splicemachine.com/how-it-works

Developer

Google

acquired by Google 2014

Hibernating Rhinos

Snowflake Computing Inc.

Splice Machine

Alex Kashirin

Initial release

2012

2010

2014

2020

Current release

5.4, July 2022

3.1, March 2021

0.5, April 2021

License

Commercial or Open Source

commercial

Open Source

AGPL version 3, commercial license available

commercial

Open Source

AGPL 3.0, commercial license available

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

hosted

Linux
macOS
Raspberry Pi
Windows

hosted

Linux
OS X
Solaris
Windows

Linux

Data scheme

schema-free

yes

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

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language (RQL)

yes

SQL-like query language

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

CLI Client
JDBC
ODBC

JDBC
Native Spark Datasource
ODBC

Proprietary protocol
Thrift

Supported programming languages

Java
JavaScript
Objective-C

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

JavaScript (Node.js)
Python

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

C++

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes

user defined functions

yes

Java

Triggers

Callbacks are triggered when data changes

yes

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Shared Nothhing Auto-Sharding, Columnar Partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID, Cluster-wide transaction available

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

yes, based on authentication and database rules

Authorization levels configured per client per database

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

Access rights for users, groups and roles according to SQL-standard

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