DBMS > Amazon DynamoDB vs. Hyprcubd vs. Microsoft Azure Data Explorer vs. Rockset

System Properties Comparison Amazon DynamoDB vs. Hyprcubd vs. Microsoft Azure Data Explorer vs. Rockset

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Editorial information provided by DB-Engines

Name

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

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

Serverless Time Series DBMS

Fully managed big data interactive analytics platform

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Primary database model

Document store
Key-value store

Time Series DBMS

Relational DBMS

column oriented

Document store

Secondary database models

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

Relational DBMS
Search engine

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	70.06
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	3.28
Rank	#83	Overall
	#45	Relational DBMS

Score	1.07
Rank	#180	Overall
	#31	Document stores

Website

aws.amazon.com/dynamodb

hyprcubd.com (offline)

azure.microsoft.com/services/data-explorer

rockset.com

Technical documentation

docs.aws.amazon.com/dynamodb

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

docs.rockset.com

Developer

Amazon

Hyprcubd, Inc.

Microsoft

Rockset

Initial release

2012

2019

Current release

cloud service with continuous releases

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

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

Data scheme

schema-free

yes

Fixed schema with schema-less datatypes (dynamic)

schema-free

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

yes

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

dynamic typing

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

ingestion from XML files supported

Secondary indexes

yes

all fields are automatically indexed

SQL

Support of SQL

SQL-like query language

Kusto Query Language (KQL), SQL subset

Read-only SQL queries, including JOINs

APIs and other access methods

RESTful HTTP API

gRPC (https)

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

HTTP REST

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

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

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Yes, possible languages: KQL, Python, R

Triggers

yes

by integration with AWS Lambda

yes

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

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

yes

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

Eventual Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

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

Concurrency

Support for concurrent manipulation of data

yes

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.

User concepts

Access control

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

token access

Azure Active Directory Authentication

Access rights for users and organizations can be defined via Rockset console

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