DBMS > Alibaba Cloud MaxCompute vs. Brytlyt vs. Hive vs. KairosDB vs. MariaDB

System Properties Comparison Alibaba Cloud MaxCompute vs. Brytlyt vs. Hive vs. KairosDB vs. MariaDB

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

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Distributed Time Series DBMS based on Cassandra or H2

MySQL application compatible open source RDBMS, enhanced with high availability, security, interoperability and performance capabilities. MariaDB ColumnStore provides a column-oriented storage engine and MariaDB Xpand supports distributed SQL.

Primary database model

Relational DBMS

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

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS

with OQGraph storage engine
Spatial DBMS

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

Score	0.77
Rank	#214	Overall
	#98	Relational DBMS

Score	0.29
Rank	#288	Overall
	#131	Relational DBMS

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Score	93.21
Rank	#13	Overall
	#9	Relational DBMS

Website

www.alibabacloud.com/product/maxcompute

brytlyt.io

hive.apache.org

github.com/kairosdb/kairosdb

mariadb.com

Site of MariaDB Corporation
mariadb.org

Site of MariaDB Foundation

Technical documentation

www.alibabacloud.com/help/en/maxcompute

docs.brytlyt.io

cwiki.apache.org/confluence/display/Hive/Home

kairosdb.github.io

mariadb.com/kb/en/library

Developer

Alibaba

Brytlyt

Apache Software Foundation

initially developed by Facebook

MariaDB Corporation Ab (MariaDB Enterprise),
MariaDB Foundation (community MariaDB Server)

The lead developer Monty Widenius is the original author of MySQL

Initial release

2016

2012

2013

2009

Fork of MySQL, which was first released in 1995

Current release

5.0, August 2023

3.1.3, April 2022

1.2.2, November 2018

11.3.2, February 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

Apache 2.0

Open Source

GPL version 2, commercial enterprise subscription 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, C++ and CUDA

Java

C and C++

Server operating systems

hosted

Linux
OS X
Windows

All OS with a Java VM

Linux
OS X
Windows

FreeBSD
Linux
Solaris
Windows

ColumnStore storage engine not available on Windows

Data scheme

yes

schema-free

yes

Dynamic columns are supported

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

specific XML-type available, but no XML query functionality.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

SQL-like DML and DDL statements

yes

with proprietary extensions

APIs and other access methods

Fluentd
Flume
MaxCompute Console

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JDBC
ODBC
Thrift

Graphite protocol
HTTP REST
Telnet API

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Java

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

C++
Java
PHP
Python

Java
JavaScript

Node.js
PHP
Python

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

Server-side scripts

Stored procedures

user defined functions

in Java

user defined functions

in PL/pgSQL

yes

user defined functions and integration of map-reduce

yes

PL/SQL compatibility added with version 10.3

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

based on Cassandra

several options for horizontal partitioning and Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Source-replica replication

selectable replication factor

based on Cassandra

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

not for in-memory storage engine

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

with MEMORY storage engine

User concepts

Access control

Access rights for users and roles

fine grained access rights according to SQL-standard

Access rights for users, groups and roles

simple password-based access control

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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