DBMS > Apache Phoenix vs. Google BigQuery vs. RDF4J vs. Sqrrl

System Properties Comparison Apache Phoenix vs. Google BigQuery vs. RDF4J vs. Sqrrl

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Editorial information provided by DB-Engines

Name

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.

Description

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

Large scale data warehouse service with append-only tables

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Adaptable, secure NoSQL built on Apache Accumulo

Primary database model

Relational DBMS

RDF store

Document store
Graph DBMS
Key-value store
Wide column store

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

Score	2.06
Rank	#123	Overall
	#58	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Website

phoenix.apache.org

cloud.google.com/bigquery

rdf4j.org

sqrrl.com

Technical documentation

phoenix.apache.org

cloud.google.com/bigquery/docs

rdf4j.org/documentation

Developer

Apache Software Foundation

Google

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Amazon

originally Sqrrl Data, Inc.

Initial release

2014

2010

2004

2012

Current release

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

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

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

Java

Server operating systems

Linux
Unix
Windows

hosted

Linux
OS X
Unix
Windows

Linux

Data scheme

yes

late-bound, schema-on-read capabilities

yes

RDF Schemas

schema-free

Typing

predefined data types such as float or date

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

yes

APIs and other access methods

JDBC

RESTful HTTP/JSON API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Supported programming languages

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

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Java
PHP
Python

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

making use of Hadoop

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

selectable replication factor

making use of Hadoop

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Immediate Consistency

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

ACID

Isolation support depends on the API used

Atomic updates per row, document, or graph entity

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

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 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)

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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