DBMS > Amazon DynamoDB vs. Firebolt vs. Microsoft Access vs. PlanetScale

System Properties Comparison Amazon DynamoDB vs. Firebolt vs. Microsoft Access vs. PlanetScale

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

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

Highly scalable cloud data warehouse and analytics product

Forked from Clickhouse

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

Scalable, distributed, serverless MySQL database platform built on top of Vitess

Primary database model

Document store
Key-value store

Relational DBMS

Secondary database models

Document store
Spatial 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	1.90
Rank	#134	Overall
	#62	Relational DBMS

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Score	1.59
Rank	#151	Overall
	#70	Relational DBMS

Website

aws.amazon.com/dynamodb

www.firebolt.io

www.microsoft.com/en-us/microsoft-365/access

planetscale.com

Technical documentation

docs.aws.amazon.com/dynamodb

docs.firebolt.io

developer.microsoft.com/en-us/access

planetscale.com/docs

Developer

Amazon

Firebolt Analytics Inc.

Microsoft

PlanetScale

Initial release

2012

2020

1992

2020

Current release

1902 (16.0.11328.20222), March 2019

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Bundled with Microsoft Office

commercial

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

C++

Server operating systems

hosted

Windows

Not a real database server, but making use of DLLs

Docker
Linux
macOS

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

Secondary indexes

yes

SQL

Support of SQL

yes

but not compliant to any SQL standard

yes

with proprietary extensions

APIs and other access methods

RESTful HTTP API

.Net
ODBC
RESTful HTTP API

ADO.NET
DAO
ODBC
OLE DB

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Go
JavaScript (Node.js)
Python

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

since Access 2010 using the ACE-engine

yes

proprietary syntax

Triggers

yes

by integration with AWS Lambda

yes

since Access 2010 using the ACE-engine

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on storage layer

none

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)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

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

ACID

but no files for transaction logging

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

but no files for transaction logging

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)

a simple user-level security was built in till version Access 2003

Users with fine-grained authorization concept

no user groups or roles

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.