DBMS > Apache Phoenix vs. GridDB vs. MySQL vs. Yanza

System Properties Comparison Apache Phoenix vs. GridDB vs. MySQL vs. Yanza

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Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

Scalable in-memory time series database optimized for IoT and Big Data

Widely used open source RDBMS

Time Series DBMS for IoT Applications

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

Time Series DBMS

Secondary database models

Key-value store
Relational DBMS

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	1.95
Rank	#128	Overall
	#10	Time Series DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Website

phoenix.apache.org

griddb.net

www.mysql.com

yanza.com

Technical documentation

phoenix.apache.org

docs.griddb.net

dev.mysql.com/doc

Developer

Apache Software Foundation

Toshiba Corporation

Oracle

since 2010, originally MySQL AB, then Sun

Yanza

Initial release

2014

2013

1995

2015

Current release

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

5.1, August 2022

8.3.0, January 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

free version available

Cloud-based only

Only available as a cloud service

but mainly used as a service provided by Yanza

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Implementation language

Java

C++

C and C++

Server operating systems

Linux
Unix
Windows

Linux

FreeBSD
Linux
OS X
Solaris
Windows

Windows

Data scheme

yes

late-bound, schema-on-read capabilities

yes

schema-free

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

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

SQL92, SQL-like TQL (Toshiba Query Language)

yes

with proprietary extensions

APIs and other access methods

JDBC

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP API

Supported programming languages

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

C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

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

any language that supports HTTP calls

Server-side scripts

Stored procedures

user defined functions

yes

proprietary syntax

Triggers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Immediate consistency within container, eventual consistency across containers

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

ACID at container level

ACID

not for MyISAM storage engine

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

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 can be defined per database

Users with fine-grained authorization concept

no user groups or roles

More information provided by the system vendor

Specific characteristics

GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more

Competitive advantages

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more

Typical application scenarios

Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more

Key customers

Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more

Market metrics

GitHub trending repository
» more

Licensing and pricing models

Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.