DBMS > Apache Phoenix vs. EsgynDB vs. etcd vs. Hypertable

System Properties Comparison Apache Phoenix vs. EsgynDB vs. etcd 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

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

A distributed reliable key-value store

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

Primary database model

Relational DBMS

Key-value store

Wide column store

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

Score	1.90
Rank	#125	Overall
	#59	Relational DBMS

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

Score	7.05
Rank	#53	Overall
	#5	Key-value stores

Website

phoenix.apache.org

www.esgyn.cn

etcd.io
github.com/etcd-io/etcd

Technical documentation

phoenix.apache.org

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

Developer

Apache Software Foundation

Esgyn

Hypertable Inc.

Initial release

2014

2015

2009

Current release

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

3.4, August 2019

0.9.8.11, March 2016

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache Version 2.0

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++, Java

C++

Server operating systems

Linux
Unix
Windows

Linux

FreeBSD
Linux
Windows

experimental

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

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

APIs and other access methods

JDBC

ADO.NET
JDBC
ODBC

gRPC
JSON over HTTP

C++ API
Thrift

Supported programming languages

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

All languages supporting JDBC/ODBC/ADO.Net

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

C++
Java
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures

Triggers

yes, watching key changes

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

Multi-source replication between multi datacenters

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

selectable replication factor on file system level

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

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