DBMS > Hypertable vs. Microsoft Azure SQL Database vs. Snowflake vs. YDB

System Properties Comparison Hypertable vs. Microsoft Azure SQL Database vs. Snowflake vs. YDB

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Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

An open source BigTable implementation based on distributed file systems such as Hadoop

Database as a Service offering with high compatibility to Microsoft SQL Server

Cloud-based data warehousing service for structured and semi-structured data

A distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API

Primary database model

Wide column store

Relational DBMS

Document store
Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	76.78
Rank	#16	Overall
	#11	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.33
Rank	#287	Overall
	#43	Document stores
	#132	Relational DBMS

Website

azure.microsoft.com/en-us/products/azure-sql/database

www.snowflake.com

github.com/ydb-platform/ydb
ydb.tech

Technical documentation

docs.microsoft.com/en-us/azure/azure-sql

docs.snowflake.net/manuals/index.html

ydb.tech/en/docs

Developer

Hypertable Inc.

Microsoft

Snowflake Computing Inc.

Yandex

Initial release

2009

2010

2014

2019

Current release

0.9.8.11, March 2016

V12

License

Commercial or Open Source

Open Source

GNU version 3. Commercial license available

commercial

Open Source

Apache 2.0; commercial license available

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

Linux
OS X
Windows

an inofficial Windows port is available

hosted

Linux

Data scheme

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

Flexible Schema (defined schema, partial schema, schema free)

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.

yes

Secondary indexes

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

yes

SQL-like query language (YQL)

APIs and other access methods

C++ API
Thrift

ADO.NET
JDBC
ODBC

CLI Client
JDBC
ODBC

RESTful HTTP API (DynamoDB compatible)

Supported programming languages

C++
Java
Perl
PHP
Python
Ruby

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

JavaScript (Node.js)
Python

Go
Java
JavaScript (Node.js)
PHP
Python

Server-side scripts

Stored procedures

Transact SQL

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor on file system level

yes, with always 3 replicas available

yes

Active-passive shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

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

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept, user roles and pluggable authentication

Access rights defined for Yandex Cloud users

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