DBMS > Amazon DynamoDB vs. LevelDB vs. Microsoft Access vs. Riak KV vs. TerarkDB

System Properties Comparison Amazon DynamoDB vs. LevelDB vs. Microsoft Access vs. Riak KV vs. TerarkDB

Editorial information provided by DB-Engines

Name

Description

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

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

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.)

Distributed, fault tolerant key-value store

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Document store
Key-value store

Key-value store

Relational DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Key-value store

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	2.25
Rank	#115	Overall
	#19	Key-value stores

Score	101.16
Rank	#11	Overall
	#8	Relational DBMS

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Score	0.08
Rank	#367	Overall
	#56	Key-value stores

Website

aws.amazon.com/dynamodb

github.com/google/leveldb

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

github.com/bytedance/terarkdb

Technical documentation

docs.aws.amazon.com/dynamodb

github.com/google/leveldb/blob/main/doc/index.md

developer.microsoft.com/en-us/access

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

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Amazon

Google

Microsoft

OpenSource, formerly Basho Technologies

ByteDance, originally Terark

Initial release

2012

2011

1992

2009

2016

Current release

1.23, February 2021

1902 (16.0.11328.20222), March 2019

3.2.0, December 2022

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

BSD

commercial

Bundled with Microsoft Office

Open Source

Apache version 2, commercial enterprise edition

commercial

restricted open source version available

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++

Erlang

C++

Server operating systems

hosted

Illumos
Linux
OS X
Windows

Windows

Not a real database server, but making use of DLLs

Linux
OS X

Data 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

SQL

Support of SQL

yes

but not compliant to any SQL standard

APIs and other access methods

RESTful HTTP API

ADO.NET
DAO
ODBC
OLE DB

HTTP API
Native Erlang Interface

C++ API
Java API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

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

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

C++
Java

Server-side scripts

Stored procedures

yes

since Access 2010 using the ACE-engine

Erlang

Triggers

yes

by integration with AWS Lambda

yes

since Access 2010 using the ACE-engine

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

no "single point of failure"

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

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

yes, using Riak Security

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