DBMS > Faircom EDGE vs. Google BigQuery vs. LevelDB vs. OpenTSDB

System Properties Comparison Faircom EDGE vs. Google BigQuery vs. LevelDB vs. OpenTSDB

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Editorial information provided by DB-Engines

Name

Description

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

Large scale data warehouse service with append-only tables

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Scalable Time Series DBMS based on HBase

Primary database model

Key-value store
Relational DBMS

Relational DBMS

Key-value store

Time Series DBMS

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

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

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	2.25
Rank	#115	Overall
	#19	Key-value stores

Score	1.68
Rank	#142	Overall
	#12	Time Series DBMS

Website

www.faircom.com/products/faircom-edge

cloud.google.com/bigquery

github.com/google/leveldb

opentsdb.net

Technical documentation

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

cloud.google.com/bigquery/docs

github.com/google/leveldb/blob/main/doc/index.md

opentsdb.net/docs/build/html/index.html

Developer

FairCom Corporation

Google

currently maintained by Yahoo and other contributors

Initial release

1979

2010

2011

Current release

V3, October 2020

1.23, February 2021

License

Commercial or Open Source

commercial

Restricted, free version available

commercial

Open Source

BSD

Open Source

LGPL

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++

Java

Server operating systems

Android
Linux

ARM, x86
Raspbian
Windows

hosted

Illumos
Linux
OS X
Windows

Linux
Windows

Data scheme

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

yes

schema-free

Typing

predefined data types such as float or date

yes, ANSI Standard SQL Types

yes

numeric data for metrics, strings for tags

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

yes

APIs and other access methods

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

RESTful HTTP/JSON API

HTTP API
Telnet API

Supported programming languages

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

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

Erlang
Go
Java
Python
R
Ruby

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

user defined functions

in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning

Customizable business rules for partitioning

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

none

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable Consistency

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

when using SQL

Transaction concepts

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

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

with automatic compression on writes

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

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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