DBMS > Alibaba Cloud Table Store vs. Faircom EDGE vs. FoundationDB vs. Google BigQuery

System Properties Comparison Alibaba Cloud Table Store vs. Faircom EDGE vs. FoundationDB vs. Google BigQuery

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Editorial information provided by DB-Engines

Name

Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.

Description

A fully managed Wide Column Store for large quantities of semi-structured data with real-time access

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

Ordered key-value store. Core features are complimented by layers.

Large scale data warehouse service with append-only tables

Primary database model

Wide column store

Key-value store
Relational DBMS

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Relational DBMS

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

Score	0.31
Rank	#297	Overall
	#11	Wide column stores

Score	0.09
Rank	#362	Overall
	#53	Key-value stores
	#155	Relational DBMS

Score	1.06
Rank	#185	Overall
	#31	Document stores
	#28	Key-value stores
	#85	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Website

www.alibabacloud.com/product/table-store

www.faircom.com/products/faircom-edge

github.com/apple/foundationdb

cloud.google.com/bigquery

Technical documentation

www.alibabacloud.com/help/en/tablestore

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

apple.github.io/foundationdb

cloud.google.com/bigquery/docs

Developer

Alibaba

FairCom Corporation

FoundationDB

Google

Initial release

2016

1979

2013

2010

Current release

V3, October 2020

6.2.28, November 2020

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

ANSI C, C++

C++

Server operating systems

hosted

Android
Linux

ARM, x86
Raspbian
Windows

Linux
OS X
Windows

hosted

Data scheme

schema-free

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

schema-free

some layers support schemas

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

some layers support typing

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

yes

ANSI SQL queries

supported in specific SQL layer only

yes

APIs and other access methods

HTTP API

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

RESTful HTTP/JSON API

Supported programming languages

Java
Python

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

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

in SQL-layer only

user defined functions

in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

File partitioning

Customizable business rules for partitioning

Sharding

none

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

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency
Tunable Consistency

Linearizable consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

when using SQL

in SQL-layer only

Transaction concepts

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

Atomic single-row operations

ACID

Since BigQuery is designed for querying data

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 based on subaccounts and tokens

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

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

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