DBMS > Alibaba Cloud MaxCompute vs. Kingbase vs. Manticore Search vs. MySQL vs. Solr

System Properties Comparison Alibaba Cloud MaxCompute vs. Kingbase vs. Manticore Search vs. MySQL vs. Solr

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

An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.

Multi-storage database for search, including full-text search.

Widely used open source RDBMS

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

Primary database model

Relational DBMS

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

Relational DBMS

Search engine

Relational DBMS

Key/Value like access via memcached API

Search engine

Secondary database models

Document store
Spatial DBMS

Time Series DBMS

using the Manticore Columnar Library

Document store
Spatial DBMS

Spatial DBMS

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

Score	0.84
Rank	#209	Overall
	#98	Relational DBMS

Score	0.50
Rank	#257	Overall
	#119	Relational DBMS

Score	0.29
Rank	#302	Overall
	#21	Search engines

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	41.02
Rank	#24	Overall
	#3	Search engines

Website

www.alibabacloud.com/product/maxcompute

Technical documentation

www.alibabacloud.com/help/en/maxcompute

manual.manticoresearch.com

dev.mysql.com/doc

solr.apache.org/resources.html

Developer

Alibaba

BeiJing KINGBASE Information technologies inc.

Manticore Software

Oracle

since 2010, originally MySQL AB, then Sun

Apache Software Foundation

Initial release

2016

1999

2017

1995

2006

Current release

V8.0, August 2021

6.0, February 2023

8.4.0, April 2024

9.6.1, May 2024

License

Commercial or Open Source

commercial

Open Source

GPL version 2

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache Version 2

Cloud-based only

Only available as a cloud service

yes

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Database as a Service

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Implementation language

C and Java

C++

C and C++

Java

Server operating systems

hosted

Linux
Windows

FreeBSD
Linux
macOS
Windows

FreeBSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

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

Data scheme

yes

Fixed schema

yes

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

Typing

predefined data types such as float or date

yes

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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

Can index from XML

yes

Secondary indexes

yes

full-text index on all search fields

yes

All search fields are automatically indexed

SQL

Support of SQL

SQL-like query language

Standard with numerous extensions

SQL-like query language

yes

with proprietary extensions

Solr Parallel SQL Interface

APIs and other access methods

Fluentd
Flume
MaxCompute Console

ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

ADO.NET
JDBC
ODBC
Proprietary native API

Java API
RESTful HTTP/JSON API

Supported programming languages

Java

.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

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

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

Server-side scripts

Stored procedures

user defined functions

in Java

user defined functions

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 (by range, list and hash) and vertical partitioning

Sharding

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

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

Synchronous replication based on Galera library

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

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

yes

isolated transactions for atomic changes and binary logging for safe writes

ACID

not for MyISAM storage engine

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

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

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

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

yes

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