DBMS > Amazon DynamoDB vs. Apache Drill vs. Google Cloud Datastore vs. NuoDB

System Properties Comparison Amazon DynamoDB vs. Apache Drill vs. Google Cloud Datastore vs. NuoDB

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Editorial information provided by DB-Engines

Name

Description

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

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

NuoDB is a webscale distributed database that supports SQL and ACID transactions

Primary database model

Document store
Key-value store

Document store
Relational DBMS

Document store

Relational 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	1.95
Rank	#127	Overall
	#23	Document stores
	#60	Relational DBMS

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	0.89
Rank	#198	Overall
	#92	Relational DBMS

Website

aws.amazon.com/dynamodb

drill.apache.org

cloud.google.com/datastore

www.3ds.com/nuodb-distributed-sql-database

Technical documentation

docs.aws.amazon.com/dynamodb

drill.apache.org/docs

cloud.google.com/datastore/docs

doc.nuodb.com

Developer

Amazon

Apache Software Foundation

Google

Dassault Systèmes

originally NuoDB, Inc.

Initial release

2012

2008

2013

Current release

1.20.3, January 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache Version 2

commercial

limited edition free

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

Linux
OS X
Windows

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, details here

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

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

SQL-like query language (GQL)

yes

APIs and other access methods

RESTful HTTP API

JDBC
ODBC
RESTful HTTP API

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C++

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

user defined functions

using Google App Engine

Java, SQL

Triggers

yes

by integration with AWS Lambda

Callbacks using the Google Apps Engine

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

data is dynamically stored/cached on the nodes where it is read/written

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication using Paxos

yes

Managed transparently by NuoDB

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

none

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

ACID

tunable commit protocol

Concurrency

Support for concurrent manipulation of data

yes

MVCC

Durability

Support for making data persistent

yes

Depending on the underlying data source

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

Depending on the underlying data source

yes

Temporary table

User concepts

Access control

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

Depending on the underlying data source

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Standard SQL roles/ privileges, Administrative Users

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