DBMS > Amazon DynamoDB vs. Blueflood vs. Firebase Realtime Database vs. Geode vs. TimescaleDB

System Properties Comparison Amazon DynamoDB vs. Blueflood vs. Firebase Realtime Database vs. Geode vs. TimescaleDB

Editorial information provided by DB-Engines

Name

Description

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

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.

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Document store
Key-value store

Secondary database models

Relational 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	0.13
Rank	#346	Overall
	#33	Time Series DBMS

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	1.86
Rank	#134	Overall
	#24	Key-value stores

Score	4.46
Rank	#71	Overall
	#5	Time Series DBMS

Website

aws.amazon.com/dynamodb

blueflood.io

firebase.google.com/products/realtime-database

geode.apache.org

www.timescale.com

Technical documentation

docs.aws.amazon.com/dynamodb

github.com/rax-maas/blueflood/wiki

firebase.google.com/docs/database

geode.apache.org/docs

docs.timescale.com

Developer

Amazon

Rackspace

Google

acquired by Google 2014

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Timescale

Initial release

2012

2013

2012

2002

2017

Current release

1.1, February 2017

2.15.0, May 2024

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache 2.0

commercial

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

Apache 2.0

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

Server operating systems

hosted

Linux
OS X

hosted

All OS with a Java VM

the JDK (8 or later) is also required

Linux
OS X
Windows

Data scheme

schema-free

predefined scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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 (OQL)

yes

full PostgreSQL SQL syntax

APIs and other access methods

RESTful HTTP API

HTTP REST

Android
iOS
JavaScript API
RESTful HTTP API

Java Client API
Memcached protocol
RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Java
JavaScript
Objective-C

.Net
All JVM based languages
C++
Groovy
Java
Scala

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

limited functionality with using 'rules'

user defined functions

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

by integration with AWS Lambda

Callbacks are triggered when data changes

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on Cassandra

Multi-source replication

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

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

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

yes, on a single node

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

yes, based on authentication and database rules

Access rights per client and object definable

fine grained access rights according to SQL-standard

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