DBMS > Apache Phoenix vs. GridDB vs. Hypertable

System Properties Comparison Apache Phoenix vs. GridDB vs. Hypertable

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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

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

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

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

Primary database model

Relational DBMS

Time Series DBMS

Wide column store

Secondary database models

Key-value store
Relational DBMS

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

Score	1.90
Rank	#125	Overall
	#59	Relational DBMS

Score	1.91
Rank	#123	Overall
	#10	Time Series DBMS

Website

phoenix.apache.org

griddb.net

Technical documentation

phoenix.apache.org

docs.griddb.net

Developer

Apache Software Foundation

Toshiba Corporation

Hypertable Inc.

Initial release

2014

2013

2009

Current release

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

5.1, August 2022

0.9.8.11, March 2016

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

GNU version 3. Commercial license available

Cloud-based only

Only available as a cloud service

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
Unix
Windows

Linux

Linux
OS X
Windows

an inofficial Windows port is available

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

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

restricted

only exact value or prefix value scans

SQL

Support of SQL

yes

SQL92, SQL-like TQL (Toshiba Query Language)

APIs and other access methods

JDBC

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

C++ API
Thrift

Supported programming languages

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

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

C++
Java
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

selectable replication factor on file system level

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

yes

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

Transaction concepts

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

ACID

ACID at container level

Concurrency

Support for concurrent manipulation of data

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

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