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

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

Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

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

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
Key-value store

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	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	2.84
Rank	#101	Overall
	#18	Document stores

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Website

aws.amazon.com/dynamodb

firebase.google.com/products/realtime-database

ravendb.net

splicemachine.com

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

Technical documentation

docs.aws.amazon.com/dynamodb

firebase.google.com/docs/database

ravendb.net/docs

splicemachine.com/how-it-works

Developer

Amazon

Google

acquired by Google 2014

Hibernating Rhinos

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

free tier for a limited amount of database operations

commercial

Open Source

AGPL version 3, commercial license available

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

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++

Server operating systems

hosted

Linux
macOS
Raspberry Pi
Windows

Linux
OS X
Solaris
Windows

Linux

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

SQL-like query language (RQL)

yes

SQL-like query language

APIs and other access methods

RESTful HTTP API

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

JDBC
Native Spark Datasource
ODBC

Proprietary protocol
Thrift

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Java
JavaScript
Objective-C

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

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

C++

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes

Java

Triggers

yes

by integration with AWS Lambda

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Shared Nothhing Auto-Sharding, Columnar Partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

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

ACID

ACID across one or more tables within a single AWS account and region

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

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

yes, based on authentication and database rules

Authorization levels configured per client per database

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

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