DBMS > Blueflood vs. Firebase Realtime Database vs. Riak TS vs. SAP HANA vs. SwayDB

System Properties Comparison Blueflood vs. Firebase Realtime Database vs. Riak TS vs. SAP HANA vs. SwayDB

Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

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

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

In-memory, column based data store. Available as appliance or cloud service

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	0.13
Rank	#346	Overall
	#33	Time Series DBMS

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	0.04
Rank	#387	Overall
	#61	Key-value stores

Website

blueflood.io

firebase.google.com/products/realtime-database

www.sap.com/products/hana.html

swaydb.simer.au

Technical documentation

github.com/rax-maas/blueflood/wiki

firebase.google.com/docs/database

www.tiot.jp/riak-docs/riak/ts/latest

help.sap.com/hana

Developer

Rackspace

Google

acquired by Google 2014

Open Source, formerly Basho Technologies

SAP

Simer Plaha

Initial release

2013

2012

2015

2010

2018

Current release

3.0.0, September 2022

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

commercial

Open Source

GNU Affero GPL V3.0

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Erlang

Scala

Server operating systems

Linux
OS X

hosted

Linux
OS X

Appliance or cloud-service

Data scheme

predefined 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

restricted

yes

SQL

Support of SQL

yes, limited

yes

APIs and other access methods

HTTP REST

Android
iOS
JavaScript API
RESTful HTTP API

HTTP API
Native Erlang Interface

JDBC
ODBC

Supported programming languages

Java
JavaScript
Objective-C

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Java
Kotlin
Scala

Server-side scripts

Stored procedures

limited functionality with using 'rules'

Erlang

SQLScript, R

Triggers

Callbacks are triggered when data changes

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

selectable replication factor

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

links between datasets can be stored

yes

Transaction concepts

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

yes

ACID

Atomic execution of operations

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

yes, based on authentication and database rules

yes

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