DBMS > Amazon DynamoDB vs. Databend vs. Firebase Realtime Database vs. Prometheus vs. Warp 10

System Properties Comparison Amazon DynamoDB vs. Databend vs. Firebase Realtime Database vs. Prometheus vs. Warp 10

Editorial information provided by DB-Engines

Name

Description

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

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

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 Time Series DBMS and monitoring system

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

Primary database model

Document store
Key-value store

Relational DBMS

Document store

Time Series DBMS

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

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.30
Rank	#287	Overall
	#130	Relational DBMS

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	8.42
Rank	#47	Overall
	#2	Time Series DBMS

Score	0.07
Rank	#349	Overall
	#32	Time Series DBMS

Website

aws.amazon.com/dynamodb

github.com/datafuselabs/databend
www.databend.com

firebase.google.com/products/realtime-database

prometheus.io

www.warp10.io

Technical documentation

docs.aws.amazon.com/dynamodb

docs.databend.com

firebase.google.com/docs/database

prometheus.io/docs

www.warp10.io/content/02_Getting_started

Developer

Amazon

Databend Labs

Google

acquired by Google 2014

SenX

Initial release

2012

2021

2012

2015

Current release

1.0.59, April 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache Version 2.0

commercial

Open Source

Apache 2.0

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

Rust

Java

Server operating systems

hosted

hosted
Linux
macOS

hosted

Linux
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data only

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.

Import of XML data possible

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP API

CLI Client
JDBC
RESTful HTTP API

Android
iOS
JavaScript API
RESTful HTTP API

RESTful HTTP/JSON API

HTTP API
Jupyter
WebSocket

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Go
Java
JavaScript (Node.js)
Python
Rust

Java
JavaScript
Objective-C

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes

WarpScript

Triggers

yes

by integration with AWS Lambda

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes

by Federation

selectable replication factor

based on HBase

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

Immediate Consistency

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

none

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

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

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)

Users with fine-grained authorization concept, user roles

yes, based on authentication and database rules

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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