DBMS > Alibaba Cloud MaxCompute vs. atoti vs. Kyligence Enterprise vs. Newts vs. Vertica

System Properties Comparison Alibaba Cloud MaxCompute vs. atoti vs. Kyligence Enterprise vs. Newts vs. Vertica

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 in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

A distributed analytics engine for big data, built on top of Apache Kylin

Time Series DBMS based on Cassandra

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Relational DBMS

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

Column oriented

Secondary database models

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	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	0.40
Rank	#269	Overall
	#124	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	10.68
Rank	#43	Overall
	#27	Relational DBMS

Website

www.alibabacloud.com/product/maxcompute

atoti.io

kyligence.io/kyligence-enterprise

opennms.github.io/newts

www.vertica.com

Technical documentation

www.alibabacloud.com/help/en/maxcompute

docs.atoti.io

github.com/OpenNMS/newts/wiki

vertica.com/documentation

Developer

Alibaba

ActiveViam

Kyligence, Inc.

OpenNMS Group

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2016

2014

2005

Current release

12.0.3, January 2023

License

Commercial or Open Source

commercial

free versions available

commercial

Open Source

Apache 2.0

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

yes

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

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

Linux
OS X
Windows

Linux

Data scheme

yes

schema-free

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

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.

Secondary indexes

yes

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

SQL-like query language

Multidimensional Expressions (MDX)

ANSI SQL for queries (using Apache Calcite)

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

Fluentd
Flume
MaxCompute Console

JDBC
ODBC
RESTful HTTP API

HTTP REST
Java API

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

Java

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

Server-side scripts

Stored procedures

user defined functions

in Java

Python

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding, horizontal partitioning

Sharding

based on Cassandra

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

selectable replication factor

based on Cassandra

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Bi-directional Spark integration

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

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

More information provided by the system vendor

Specific characteristics

Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more

Competitive advantages

Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more

Typical application scenarios

Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more

Key customers

Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more

Licensing and pricing models

Cost-based models and subscription-based models are both available. One license is...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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