DBMS > Amazon DynamoDB vs. atoti vs. Google BigQuery vs. TerminusDB

System Properties Comparison Amazon DynamoDB vs. atoti vs. Google BigQuery vs. TerminusDB

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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

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

Large scale data warehouse service with append-only tables

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Document store
Key-value store

Object oriented DBMS

Relational DBMS

Graph DBMS

Secondary database models

Document store
RDF 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	0.61
Rank	#243	Overall
	#10	Object oriented DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Website

aws.amazon.com/dynamodb

atoti.io

cloud.google.com/bigquery

terminusdb.com

Technical documentation

docs.aws.amazon.com/dynamodb

docs.atoti.io

cloud.google.com/bigquery/docs

terminusdb.github.io/terminusdb/#

Developer

Amazon

ActiveViam

Google

DataChemist Ltd.

Initial release

2012

2010

2018

Current release

11.0.0, January 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

free versions available

commercial

Open Source

GPL V3

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

Java

Prolog, Rust

Server operating systems

hosted

Linux

Data scheme

schema-free

yes

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

SQL

Support of SQL

Multidimensional Expressions (MDX)

yes

SQL-like query language (WOQL)

APIs and other access methods

RESTful HTTP API

RESTful HTTP/JSON API

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

JavaScript
Python

Server-side scripts

Stored procedures

Python

user defined functions

in JavaScript

yes

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

none

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Journaling Streams

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

Immediate Consistency

Foreign keys

Referential integrity

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

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

in-memory journaling

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 privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Role-based access control

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