DBMS > Apache Phoenix vs. Badger vs. EsgynDB vs. Geode

System Properties Comparison Apache Phoenix vs. Badger vs. EsgynDB vs. Geode

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Editorial information provided by DB-Engines

Name

Description

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

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

Primary database model

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

Score	2.06
Rank	#123	Overall
	#58	Relational DBMS

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	1.86
Rank	#134	Overall
	#24	Key-value stores

Website

phoenix.apache.org

github.com/dgraph-io/badger

www.esgyn.cn

geode.apache.org

Technical documentation

phoenix.apache.org

godoc.org/github.com/dgraph-io/badger

geode.apache.org/docs

Developer

Apache Software Foundation

DGraph Labs

Esgyn

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Initial release

2014

2017

2015

2002

Current release

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

1.1, February 2017

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

Open Source

Apache Version 2; commercial licenses available as Gemfire

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++, Java

Java

Server operating systems

Linux
Unix
Windows

BSD
Linux
OS X
Solaris
Windows

Linux

All OS with a Java VM

the JDK (8 or later) is also required

Data scheme

yes

late-bound, schema-on-read capabilities

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language (OQL)

APIs and other access methods

JDBC

ADO.NET
JDBC
ODBC

Java Client API
Memcached protocol
RESTful HTTP API

Supported programming languages

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

All languages supporting JDBC/ODBC/ADO.Net

.Net
All JVM based languages
C++
Groovy
Java
Scala

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures

user defined functions

Triggers

yes

Cache Event Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

Multi-source replication between multi datacenters

Multi-source replication

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

none

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes, on a single node

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

fine grained access rights according to SQL-standard

Access rights per client and object definable

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More resources

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11 August 2021, Krishna Maheshwari (sponsor)

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