DBMS > Amazon DynamoDB vs. Google Cloud Datastore vs. ITTIA vs. NSDb

System Properties Comparison Amazon DynamoDB vs. Google Cloud Datastore vs. ITTIA vs. NSDb

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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

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

Edge Time Series DBMS with Real-Time Stream Processing

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Primary database model

Document store
Key-value store

Document store

Time Series DBMS

Secondary database models

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	4.47
Rank	#76	Overall
	#12	Document stores

Score	0.39
Rank	#273	Overall
	#24	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

aws.amazon.com/dynamodb

cloud.google.com/datastore

www.ittia.com

nsdb.io

Technical documentation

docs.aws.amazon.com/dynamodb

cloud.google.com/datastore/docs

nsdb.io/Architecture

Developer

Amazon

Google

ITTIA L.L.C.

Initial release

2012

2008

2007

2017

Current release

8.7

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Open Source

Apache Version 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

C and C++

Java, Scala

Server operating systems

hosted

Linux
Windows

Linux
macOS

Data scheme

schema-free

Fixed schema

Typing

predefined data types such as float or date

yes

yes, details here

Float/Blob/Integer/String/Unicode/Date/Time/Timestamp/Interval

yes: int, bigint, decimal, string

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

all fields are automatically indexed

SQL

Support of SQL

SQL-like query language (GQL)

yes

SQL-like query language

APIs and other access methods

RESTful HTTP API

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

JDBC
ODBC
RESTful HTTP API
WebSocket

gRPC
HTTP REST
WebSocket

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

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

C
C++
JavaScript (Node.js)
Python

Java
Scala

Server-side scripts

Stored procedures

using Google App Engine

yes

Triggers

yes

by integration with AWS Lambda

Callbacks using the Google Apps Engine

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication using Paxos

yes

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

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.

Eventual 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

yes

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

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)

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

Database file passwords

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