DBMS > Alibaba Cloud MaxCompute vs. Apache Pinot vs. ClickHouse vs. Faircom EDGE vs. SwayDB

System Properties Comparison Alibaba Cloud MaxCompute vs. Apache Pinot vs. ClickHouse vs. Faircom EDGE vs. SwayDB

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

Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency

A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Relational DBMS

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

Relational DBMS

Key-value store
Relational DBMS

Key-value store

Secondary database models

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	0.40
Rank	#270	Overall
	#125	Relational DBMS

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	0.02
Rank	#368	Overall
	#54	Key-value stores
	#156	Relational DBMS

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Website

www.alibabacloud.com/product/maxcompute

pinot.apache.org

clickhouse.com

www.faircom.com/products/faircom-edge

swaydb.simer.au

Technical documentation

www.alibabacloud.com/help/en/maxcompute

docs.pinot.apache.org

clickhouse.com/docs

docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html

Developer

Alibaba

Apache Software Foundation and contributors

Clickhouse Inc.

FairCom Corporation

Simer Plaha

Initial release

2016

2015

2016

1979

2018

Current release

1.0.0, September 2023

v24.4.1.2088-stable, May 2024

V3, October 2020

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

Restricted, free version available

Open Source

GNU Affero GPL V3.0

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.

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Implementation language

Java

C++

ANSI C, C++

Scala

Server operating systems

hosted

All OS with a Java JDK11 or higher

FreeBSD
Linux
macOS

Android
Linux

ARM, x86
Raspbian
Windows

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

schema-free

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

Close to ANSI SQL (SQL/JSON + extensions)

yes

ANSI SQL queries

APIs and other access methods

Fluentd
Flume
MaxCompute Console

JDBC

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

Supported programming languages

Java

Go
Java
Python

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Rust
Scala

3rd party library

C
C#
C++
Java
JavaScript
PHP
Python
VB.Net

Java
Kotlin
Scala

Server-side scripts

Stored procedures

user defined functions

in Java

yes

.Net, JavaScript, C/C++

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

horizontal partitioning

key based and custom

File partitioning

Customizable business rules for partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

yes

Synchronous and asynchronous realtime replication based on transaction logs

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency
Tunable Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

when using SQL

Transaction concepts

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

ACID

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

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

Access rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

Fine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

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