DBMS > Alibaba Cloud MaxCompute vs. MySQL vs. RocksDB vs. Solr vs. SWC-DB

System Properties Comparison Alibaba Cloud MaxCompute vs. MySQL vs. RocksDB vs. Solr vs. SWC-DB

Editorial information provided by DB-Engines

Name

Description

MaxCompute (previously known as ODPS) is a general purpose, fully managed, multi-tenancy data processing platform for large-scale data warehousing

Widely used open source RDBMS

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

A widely used distributed, scalable search engine based on Apache Lucene

A high performance, scalable Wide Column DBMS

Primary database model

Relational DBMS

a graph-processing framework is available with the graphs being stored in tables

Relational DBMS

Key/Value like access via memcached API

Key-value store

Search engine

Wide column store

Secondary database models

Document store
Spatial DBMS

Spatial DBMS

Time Series DBMS

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

Score	0.77
Rank	#214	Overall
	#98	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	42.91
Rank	#24	Overall
	#3	Search engines

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

www.alibabacloud.com/product/maxcompute

www.mysql.com

rocksdb.org

solr.apache.org

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

www.alibabacloud.com/help/en/maxcompute

dev.mysql.com/doc

github.com/facebook/rocksdb/wiki

solr.apache.org/resources.html

Developer

Alibaba

Oracle

since 2010, originally MySQL AB, then Sun

Facebook, Inc.

Apache Software Foundation

Alex Kashirin

Initial release

2016

1995

2013

2006

2020

Current release

8.4.0, April 2024

8.11.4, April 2024

9.6.0, April 2024

0.5, April 2021

License

Commercial or Open Source

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

BSD

Open Source

Apache Version 2

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C and C++

C++

Java

C++

Server operating systems

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Linux

Data scheme

yes

schema-free

yes

Dynamic Fields enables on-the-fly addition of new fields

schema-free

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic 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

Secondary indexes

yes

All search fields are automatically indexed

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

Solr Parallel SQL Interface

SQL-like query language

APIs and other access methods

Fluentd
Flume
MaxCompute Console

ADO.NET
JDBC
ODBC
Proprietary native API

C++ API
Java API

Java API
RESTful HTTP/JSON API

Proprietary protocol
Thrift

Supported programming languages

Java

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

C
C++
Go
Java
Perl
Python
Ruby

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

C++

Server-side scripts

Stored procedures

user defined functions

in Java

yes

proprietary syntax

Java plugins

Triggers

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

yes

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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.

yes

User concepts

Access control

Access rights for users and roles

Users with fine-grained authorization concept

no user groups or roles

yes

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