DBMS > Apache Drill vs. Apache Phoenix vs. FoundationDB vs. Google BigQuery vs. mSQL

System Properties Comparison Apache Drill vs. Apache Phoenix vs. FoundationDB vs. Google BigQuery vs. mSQL

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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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

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

A scale-out RDBMS with evolutionary schema built on Apache HBase

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

Large scale data warehouse service with append-only tables

mSQL (Mini SQL) is a simple and lightweight RDBMS

Primary database model

Document store
Relational DBMS

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	2.02
Rank	#124	Overall
	#22	Document stores
	#59	Relational DBMS

Score	2.06
Rank	#123	Overall
	#58	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

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Website

drill.apache.org

phoenix.apache.org

github.com/apple/foundationdb

cloud.google.com/bigquery

hughestech.com.au/products/msql

Technical documentation

drill.apache.org/docs

phoenix.apache.org

apple.github.io/foundationdb

cloud.google.com/bigquery/docs

Developer

Apache Software Foundation

FoundationDB

Google

Hughes Technologies

Initial release

2012

2014

2013

2010

1994

Current release

1.20.3, January 2023

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

6.2.28, November 2020

4.4, October 2021

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

free licenses can be provided

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

Java

C++

Server operating systems

Linux
OS X
Windows

Linux
Unix
Windows

Linux
OS X
Windows

hosted

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

schema-free

yes

late-bound, schema-on-read capabilities

schema-free

some layers support schemas

yes

Typing

predefined data types such as float or date

yes

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.

Secondary indexes

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes

supported in specific SQL layer only

yes

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

JDBC

RESTful HTTP/JSON API

JDBC
ODBC

Supported programming languages

C++

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C++
Delphi
Java
Perl
PHP
Tcl

Server-side scripts

Stored procedures

user defined functions

in SQL-layer only

user defined functions

in JavaScript

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency or Eventual Consistency

Linearizable consistency

Immediate Consistency

none

Foreign keys

Referential integrity

in SQL-layer only

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

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

User concepts

Access control

Depending on the underlying data source

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

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

Google Cloud Identity & Access Management (IAM)

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