DBMS > Alibaba Cloud AnalyticDB for MySQL vs. Amazon DocumentDB vs. Hyprcubd vs. SQLite vs. Vitess

System Properties Comparison Alibaba Cloud AnalyticDB for MySQL vs. Amazon DocumentDB vs. Hyprcubd vs. SQLite vs. Vitess

Editorial information provided by DB-Engines

Name

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

Description

A real-time data warehousing service that can process petabytes of data with high concurrency and low latency. It is fully compatible with the MySQL protocol.

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

Serverless Time Series DBMS

Widely used embeddable, in-process RDBMS

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Secondary database models

Document store

Document store
Spatial DBMS

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

Score	0.91
Rank	#201	Overall
	#94	Relational DBMS

Score	1.91
Rank	#131	Overall
	#24	Document stores

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	0.88
Rank	#203	Overall
	#95	Relational DBMS

Website

www.alibabacloud.com/product/analyticdb-for-mysql

aws.amazon.com/documentdb

hyprcubd.com (offline)

www.sqlite.org

vitess.io

Technical documentation

www.alibabacloud.com/help/doc-detail/93776.htm

aws.amazon.com/documentdb/resources

www.sqlite.org/docs.html

vitess.io/docs

Developer

Alibaba

Hyprcubd, Inc.

Dwayne Richard Hipp

The Linux Foundation, PlanetScale

Initial release

2019

2000

2013

Current release

3.46.0 (23 May 2024), May 2024

15.0.2, December 2022

License

Commercial or Open Source

commercial

Open Source

Public Domain

Open Source

Apache Version 2.0, commercial licenses 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

Server operating systems

hosted

server-less

Docker
Linux
macOS

Data scheme

yes

schema-free

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

yes

not rigid because of 'dynamic typing' concept.

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

SQL

Support of SQL

yes

SQL-like query language

yes

SQL-92 is not fully supported

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC

proprietary protocol using JSON (MongoDB compatible)

gRPC (https)

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

C#
Java
PHP
Python

Go
Java
JavaScript (Node.js)
PHP
Python

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

none

Multi-source replication
Source-replica replication

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

Immediate Consistency

Eventual Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

typically not used, however similar functionality with DBRef possible

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

Atomic single-document operations

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

yes

table locks or row locks depending on storage engine

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

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles

token access

Users with fine-grained authorization concept

no user groups or roles

More information provided by the system vendor

Specific characteristics

A real-time data warehousing service that can process PB data with high concurrency...
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Competitive advantages

TPC Benchmark: The world leading result in TPC-DS benchmark . TPC-H benchmark for...
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Licensing and pricing models

Available regions: America US Virginia US Silicon Valley Asia China Hong Kong India...
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