DBMS > Apache Drill vs. Faircom EDGE vs. Hypertable vs. Oracle NoSQL

System Properties Comparison Apache Drill vs. Faircom EDGE vs. Hypertable vs. Oracle NoSQL

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Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

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

An open source BigTable implementation based on distributed file systems such as Hadoop

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Primary database model

Document store
Relational DBMS

Key-value store
Relational DBMS

Wide column store

Document store
Key-value store
Relational DBMS

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

Score	1.90
Rank	#126	Overall
	#23	Document stores
	#60	Relational DBMS

Score	0.02
Rank	#370	Overall
	#55	Key-value stores
	#157	Relational DBMS

Score	3.07
Rank	#86	Overall
	#15	Document stores
	#11	Key-value stores
	#47	Relational DBMS

Website

drill.apache.org

www.faircom.com/products/faircom-edge

www.oracle.com/database/nosql/technologies/nosql

Technical documentation

drill.apache.org/docs

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

docs.oracle.com/en/database/other-databases/nosql-database/index.html

Developer

Apache Software Foundation

FairCom Corporation

Hypertable Inc.

Oracle

Initial release

2012

1979

2009

2011

Current release

1.20.3, January 2023

V3, October 2020

0.9.8.11, March 2016

24.1, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Restricted, free version available

Open Source

GNU version 3. Commercial license available

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

ANSI C, C++

C++

Java

Server operating systems

Linux
OS X
Windows

Android
Linux

ARM, x86
Raspbian
Windows

Linux
OS X
Windows

an inofficial Windows port is available

Linux
Solaris SPARC/x86

Data scheme

schema-free

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

schema-free

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

optional

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

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes

ANSI SQL queries

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

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

C++ API
Thrift

RESTful HTTP API

Supported programming languages

C++

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

C++
Java
Perl
PHP
Python
Ruby

C
C#
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

yes

.Net, JavaScript, C/C++

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

File partitioning

Customizable business rules for partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

selectable replication factor on file system level

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency
Tunable Consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

yes

when using SQL

Transaction concepts

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

ACID

configurable

ACID within a storage node (=shard)

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

Depending on the underlying data source

yes

off heap cache

User concepts

Access control

Depending on the underlying data source

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

Access rights for users and roles

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