DBMS > Alibaba Cloud MaxCompute vs. Amazon DocumentDB vs. Hawkular Metrics vs. Manticore Search vs. Snowflake

System Properties Comparison Alibaba Cloud MaxCompute vs. Amazon DocumentDB vs. Hawkular Metrics vs. Manticore Search vs. Snowflake

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Name

Description

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

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

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

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

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Relational DBMS

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

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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

Score	0.77
Rank	#214	Overall
	#98	Relational DBMS

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

www.alibabacloud.com/product/maxcompute

aws.amazon.com/documentdb

www.hawkular.org

manticoresearch.com

www.snowflake.com

Technical documentation

www.alibabacloud.com/help/en/maxcompute

aws.amazon.com/documentdb/resources

www.hawkular.org/hawkular-metrics/docs/user-guide

manual.manticoresearch.com

docs.snowflake.net/manuals/index.html

Developer

Alibaba

Community supported by Red Hat

Manticore Software

Snowflake Computing Inc.

Initial release

2016

2019

2014

2017

2014

Current release

6.0, February 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

GPL version 2

commercial

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

Java

C++

Server operating systems

hosted

Linux
OS X
Windows

FreeBSD
Linux
macOS
Windows

hosted

Data scheme

yes

schema-free

Fixed schema

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes

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

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.

Can index from XML

yes

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

Fluentd
Flume
MaxCompute Console

proprietary protocol using JSON (MongoDB compatible)

HTTP REST

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

CLI Client
JDBC
ODBC

Supported programming languages

Java

Go
Java
JavaScript (Node.js)
PHP
Python

Go
Java
Python
Ruby

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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

in Java

user defined functions

Triggers

yes

via Hawkular Alerting

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

Sharding

based on Cassandra

Sharding

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

yes

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

selectable replication factor

based on Cassandra

Synchronous replication based on Galera library

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

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

typically not used, however similar functionality with DBRef possible

yes

Transaction concepts

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

Atomic single-document operations

yes

isolated transactions for atomic changes and binary logging for safe writes

ACID

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 Manticore index.

yes

In-memory capabilities

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

User concepts

Access control

Access rights for users and roles

Users with fine-grained authorization concept, user roles and pluggable authentication

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