DBMS > Alibaba Cloud MaxCompute vs. Faircom EDGE vs. HarperDB vs. Hive vs. Snowflake

System Properties Comparison Alibaba Cloud MaxCompute vs. Faircom EDGE vs. HarperDB vs. Hive vs. Snowflake

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

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

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

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

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

Key-value store
Relational DBMS

Document store

Relational DBMS

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

Score	0.77
Rank	#214	Overall
	#98	Relational DBMS

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

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

www.alibabacloud.com/product/maxcompute

www.faircom.com/products/faircom-edge

www.harperdb.io

hive.apache.org

www.snowflake.com

Technical documentation

www.alibabacloud.com/help/en/maxcompute

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

docs.harperdb.io/docs

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

docs.snowflake.net/manuals/index.html

Developer

Alibaba

FairCom Corporation

HarperDB

Apache Software Foundation

initially developed by Facebook

Snowflake Computing Inc.

Initial release

2016

1979

2017

2012

2014

Current release

V3, October 2020

3.1, August 2021

3.1.3, April 2022

License

Commercial or Open Source

commercial

Restricted, free version available

commercial

free community edition available

Open Source

Apache 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

ANSI C, C++

Node.js

Java

Server operating systems

hosted

Android
Linux

ARM, x86
Raspbian
Windows

Linux
OS X

All OS with a Java VM

hosted

Data scheme

yes

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

dynamic schema

yes

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

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

yes

JSON data types

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

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

ANSI SQL queries

SQL-like data manipulation statements

SQL-like DML and DDL statements

yes

APIs and other access methods

Fluentd
Flume
MaxCompute Console

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

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

JDBC
ODBC
Thrift

CLI Client
JDBC
ODBC

Supported programming languages

Java

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

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

C++
Java
PHP
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

in Java

yes

.Net, JavaScript, C/C++

Custom Functions

since release 3.1

yes

user defined functions and integration of map-reduce

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

File partitioning

Customizable business rules for partitioning

A table resides as a whole on one (or more) nodes in a cluster

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

Synchronous and asynchronous realtime replication based on transaction logs

yes

the nodes on which a table resides can be defined

selectable replication factor

yes

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

Immediate Consistency
Tunable Consistency

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

when using SQL

yes

Transaction concepts

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

ACID

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

yes

Durability

Support for making data persistent

yes

yes, using LMDB

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

Access rights for users and roles

Access rights for users, groups and roles

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

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