DBMS > Amazon DynamoDB vs. HEAVY.AI vs. Microsoft Azure Data Explorer vs. NuoDB

System Properties Comparison Amazon DynamoDB vs. HEAVY.AI vs. Microsoft Azure Data Explorer 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

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Fully managed big data interactive analytics platform

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

Primary database model

Document store
Key-value store

Relational DBMS

column oriented

Relational DBMS

Secondary database models

Spatial DBMS

Document store

If a column is of type dynamic docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types/dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store

this is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine

support for complex search expressions docs.microsoft.com/en-us/azure/kusto/query/parseoperator FTS, Geospatial docs.microsoft.com/en-us/azure/kusto/query/geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS

see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis

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	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	3.80
Rank	#81	Overall
	#43	Relational DBMS

Score	0.94
Rank	#197	Overall
	#92	Relational DBMS

Website

aws.amazon.com/dynamodb

github.com/heavyai/heavydb
www.heavy.ai

azure.microsoft.com/services/data-explorer

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

Technical documentation

docs.aws.amazon.com/dynamodb

docs.heavy.ai

docs.microsoft.com/en-us/azure/data-explorer

doc.nuodb.com

Developer

Amazon

HEAVY.AI, Inc.

Microsoft

Dassault Systèmes

originally NuoDB, Inc.

Initial release

2012

2016

2019

2013

Current release

5.10, January 2022

cloud service with continuous releases

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache Version 2; enterprise edition available

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++ and CUDA

C++

Server operating systems

hosted

Linux

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Data scheme

schema-free

yes

Fixed schema with schema-less datatypes (dynamic)

yes

Typing

predefined data types such as float or date

yes

bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types

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.

yes

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

yes

Kusto Query Language (KQL), SQL subset

yes

APIs and other access methods

RESTful HTTP API

JDBC
ODBC
Thrift
Vega

Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API

ADO.NET
JDBC
ODBC

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

All languages supporting JDBC/ODBC/Thrift
Python

.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R

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

Server-side scripts

Stored procedures

Yes, possible languages: KQL, Python, R

Java, SQL

Triggers

yes

by integration with AWS Lambda

yes

see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

Sharding

Implicit feature of the cloud service

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

yes

Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

yes

Managed transparently by NuoDB

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Spark connector (open source): github.com/Azure/azure-kusto-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Eventual Consistency
Immediate Consistency

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

ACID

tunable commit protocol

Concurrency

Support for concurrent manipulation of data

yes

MVCC

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

Temporary table

User concepts

Access control

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

fine grained access rights according to SQL-standard

Azure Active Directory Authentication

Standard SQL roles/ privileges, Administrative Users

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