DBMS > Amazon SimpleDB vs. Badger vs. FileMaker vs. Microsoft Azure Cosmos DB vs. Prometheus

System Properties Comparison Amazon SimpleDB vs. Badger vs. FileMaker vs. Microsoft Azure Cosmos DB vs. Prometheus

Editorial information provided by DB-Engines

Name

Description

Hosted simple database service by Amazon, with the data stored in the Amazon Cloud.

There is an unrelated product called SimpleDB developed by Edward Sciore

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

FileMaker is a cross-platform RDBMS that includes a GUI frontend.

Globally distributed, horizontally scalable, multi-model database service

Open-source Time Series DBMS and monitoring system

Primary database model

Key-value store

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Time Series DBMS

Secondary database models

Spatial DBMS

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

Score	1.88
Rank	#133	Overall
	#23	Key-value stores

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	47.91
Rank	#20	Overall
	#14	Relational DBMS

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	7.69
Rank	#50	Overall
	#3	Time Series DBMS

Website

aws.amazon.com/simpledb

github.com/dgraph-io/badger

www.claris.com/filemaker

azure.microsoft.com/services/cosmos-db

prometheus.io

Technical documentation

docs.aws.amazon.com/simpledb

godoc.org/github.com/dgraph-io/badger

www.claris.com/resources/documentation

learn.microsoft.com/azure/cosmos-db

prometheus.io/docs

Developer

Amazon

DGraph Labs

Claris

a subsidiary of Apple

Microsoft

Initial release

2007

2017

1983

2014

2015

Current release

19.4.1, November 2021

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

Apache 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

Server operating systems

hosted

BSD
Linux
OS X
Solaris
Windows

iOS

client part only
Linux
OS X
Windows

hosted

Linux
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

Numeric data only

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

A http query request can return the data in XML format

Import of XML data possible

Secondary indexes

yes

All columns are indexed automatically

yes

All properties auto-indexed by default

SQL

Support of SQL

yes

via plugins

SQL-like query language

APIs and other access methods

RESTful HTTP API

Filemaker WebDirect
JDBC
ODBC

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

RESTful HTTP/JSON API

Supported programming languages

.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala

PHP

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

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

Server-side scripts

Stored procedures

yes

JavaScript

Triggers

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

none

Sharding must be implemented in the application

none

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Source-replica replication, warm standby

since Version 14

yes

Implicit feature of the cloud service

yes

by Federation

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

none

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

none

Foreign keys

Referential integrity

yes

Transaction concepts

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

Concurrent data updates can be detected by the application

Multi-item ACID transactions with snapshot isolation within a partition

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.

User concepts

Access control

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

simple rights management via user accounts and connection to external directory services

Access rights can be defined down to the item level

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