DBMS > Alibaba Cloud MaxCompute vs. Kinetica vs. Microsoft Azure Cosmos DB vs. Prometheus vs. Rockset

System Properties Comparison Alibaba Cloud MaxCompute vs. Kinetica vs. Microsoft Azure Cosmos DB vs. Prometheus vs. Rockset

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

Fully vectorized database across both GPUs and CPUs

Globally distributed, horizontally scalable, multi-model database service

Open-source Time Series DBMS and monitoring system

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Primary database model

Relational DBMS

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

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Time Series DBMS

Document store

Secondary database models

Spatial DBMS
Time Series DBMS

Spatial DBMS

Relational DBMS
Search engine

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

Score	0.84
Rank	#209	Overall
	#98	Relational DBMS

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	7.69
Rank	#50	Overall
	#3	Time Series DBMS

Score	0.82
Rank	#212	Overall
	#36	Document stores

Website

www.alibabacloud.com/product/maxcompute

www.kinetica.com

azure.microsoft.com/services/cosmos-db

prometheus.io

rockset.com

Technical documentation

www.alibabacloud.com/help/en/maxcompute

docs.kinetica.com

learn.microsoft.com/azure/cosmos-db

prometheus.io/docs

docs.rockset.com

Developer

Alibaba

Kinetica

Microsoft

Rockset

Initial release

2016

2012

2014

2015

2019

Current release

7.1, August 2021

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

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

C, C++

C++

Server operating systems

hosted

Linux

hosted

Linux
Windows

hosted

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON types

Numeric data only

dynamic 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.

Import of XML data possible

ingestion from XML files supported

Secondary indexes

yes

All properties auto-indexed by default

all fields are automatically indexed

SQL

Support of SQL

SQL-like query language

SQL-like DML and DDL statements

SQL-like query language

Read-only SQL queries, including JOINs

APIs and other access methods

Fluentd
Flume
MaxCompute Console

JDBC
ODBC
RESTful HTTP API

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

RESTful HTTP/JSON API

HTTP REST

Supported programming languages

Java

C++
Java
JavaScript (Node.js)
Python

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

in Java

user defined functions

JavaScript

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Implicit feature of the cloud service

Sharding

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Source-replica replication

yes

Implicit feature of the cloud service

yes

by Federation

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

none

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

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

GPU vRAM or System RAM

User concepts

Access control

Access rights for users and roles

Access rights for users and roles on table level

Access rights can be defined down to the item level

Access rights for users and organizations can be defined via Rockset console

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