DBMS > Alibaba Cloud AnalyticDB for MySQL vs. Amazon DynamoDB vs. HEAVY.AI vs. Sphinx

System Properties Comparison Alibaba Cloud AnalyticDB for MySQL vs. Amazon DynamoDB vs. HEAVY.AI vs. Sphinx

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Editorial information provided by DB-Engines

Name

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.

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

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Relational DBMS

Document store
Key-value store

Relational DBMS

Search engine

Secondary database models

Document store

Spatial DBMS

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

Score	0.85
Rank	#207	Overall
	#96	Relational DBMS

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

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

aws.amazon.com/dynamodb

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

sphinxsearch.com

Technical documentation

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

docs.aws.amazon.com/dynamodb

docs.heavy.ai

sphinxsearch.com/docs

Developer

Alibaba

Amazon

HEAVY.AI, Inc.

Sphinx Technologies Inc.

Initial release

2012

2016

2001

Current release

5.10, January 2022

3.5.1, February 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache Version 2; enterprise edition available

Open Source

GPL version 2, commercial licence 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++ and CUDA

C++

Server operating systems

hosted

Linux

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

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.

yes

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

yes

SQL-like query language (SphinxQL)

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

JDBC
ODBC
Thrift
Vega

Proprietary protocol

Supported programming languages

C#
Java
PHP
Python

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

All languages supporting JDBC/ODBC/Thrift
Python

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

yes

Triggers

yes

by integration with AWS Lambda

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Round robin

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

Multi-source replication

none

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
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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Sphinx index.

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 can be defined via the AWS Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

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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