DBMS > Apache Phoenix vs. Hive vs. MySQL vs. Sqrrl vs. TinkerGraph

System Properties Comparison Apache Phoenix vs. Hive vs. MySQL vs. Sqrrl vs. TinkerGraph

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

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Widely used open source RDBMS

Adaptable, secure NoSQL built on Apache Accumulo

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

Primary database model

Relational DBMS

Key/Value like access via memcached API

Document store
Graph DBMS
Key-value store
Wide column store

Graph DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.08
Rank	#348	Overall
	#35	Graph DBMS

Website

phoenix.apache.org

hive.apache.org

www.mysql.com

sqrrl.com

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

Technical documentation

phoenix.apache.org

cwiki.apache.org/confluence/display/Hive/Home

dev.mysql.com/doc

Developer

Apache Software Foundation

initially developed by Facebook

Oracle

since 2010, originally MySQL AB, then Sun

Amazon

originally Sqrrl Data, Inc.

Initial release

2014

2012

1995

2012

2009

Current release

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

3.1.3, April 2022

8.4.0, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C and C++

Java

Server operating systems

Linux
Unix
Windows

All OS with a Java VM

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Data scheme

yes

late-bound, schema-on-read capabilities

yes

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

yes

with proprietary extensions

APIs and other access methods

JDBC

JDBC
ODBC
Thrift

ADO.NET
JDBC
ODBC
Proprietary native API

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

TinkerPop 3

Supported programming languages

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

C++
Java
PHP
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Actionscript
C

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

Groovy
Java

Server-side scripts

Stored procedures

user defined functions

yes

user defined functions and integration of map-reduce

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

making use of Hadoop

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

selectable replication factor

Multi-source replication
Source-replica replication

selectable replication factor

making use of Hadoop

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Eventual Consistency

Immediate Consistency

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

none

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Relationships in graphs

Transaction concepts

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

ACID

not for MyISAM storage engine

Atomic updates per row, document, or graph entity

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

optional

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 rights for users, groups and roles

Users with fine-grained authorization concept

no user groups or roles

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

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